Systems and methods for treating disorders of the central nervous system by modulation of brain networks

ABSTRACT

The present invention involves methods and systems for treatment of brain disorders using neuromodulation that is provided to modulate structures of brain networks. Treatment occurs using electrical, optical, magnetic, and/or chemical stimulation of one or more brain networks associated with a brain disorder. The methods involve using a brain modulation system (BMS) to increase, decrease, or otherwise modulate characteristics of the regions of the network, such as relative levels of electrical activity or neurotransmitter levels. Treatment can be initiated and adjusted based upon evaluation of functional neuroimaging data for the network and brain network modeling. Linking rules may guide in adjusting the treatment protocol used to provide neuromodulation of multiple regions of a brain network. Novel methods are described for addressing issues of compensation, adaptation, and unintentional modulation due to indirect stimulation that can arise due to connectivity between structures within brain networks.

DESCRIPTION

This application claims priority of U.S. Provisional Application No.60/594,270 filed, Mar. 24, 2005, entitled “Systems and Methods forTreating Central Nervous System Disorders using Neuromodulation of BrainNetworks” which claims priority of U.S. Provisional Application No.60,593521 filed Jan. 21, 2005, entitled “Systems and Methods forTreatment of Epilepsy and Other Neurological and Psychiatric Disorders”and also claims priority of 60/595,788 filed on Aug. 5, 2005, entitled“Systems and Methods for Treating Disorders of the Central NervousSystem by Neuromodulation of Brain Networks”.

The invention relates to modulation of the central nervous system fortreating brain disorders and more particularly to modulation of brainnetworks associated with undesirable aspects or symptoms of a patient'sbrain disorder.

Various disorders of the central nervous system affect millions ofpeople annually. While a large proportion may be aided by pharmaceuticalinterventions, many are not helped by medication, or are not helpedsufficiently to provide desired levels of relief. In depression, forexample, up to ⅓ of patients may be either partially or completelyresistant to treatment. Further, choosing and adjusting the medicationsused for treatment of brain disorders, such as attention deficits withor without hyperactivity, developmental, psychiatric, mood, andneurological disorders is a complicated process with unwantedside-effects often occurring simultaneously with treatment benefits.

A number of novel technologies for assisting treatment resistantpatients have recently become commercially available. Implantableneurostimulators, providing electrical or pharmaceutical therapy areavailable from companies such as Medtronic, Advanced NeuromodulationSystems, Cyberonics, and NeuroPace. These neurostimulators are used totreat a wide variety of medical conditions including movement disorders,epilepsy, pain, depression, and other disorders of the central nervoussystem. In addition to direct electrical/pharmaceutical stimulation ofbrain tissue, transcranial magnetic stimulation and vagus nervestimulation have also shown moderate efficacy with respect to treatmentof brain disorders such as depression, migraine, and epilepsy.

Neuromodulation for treatment of brain disorders, such as movementdisorders, is quite promising and over the last 2 decades has beencarried out with increasing rates of success (Cooper et al, 1982). Forexample, recently, Yianni et al (2005) reported successful treatment of5 subjects suffering from dystonia by means of deep brain stimulation(DBS) of the globus pallidus. Psychiatric disorders are likey morecomplex than this type of pain disorder and will require morecomplicated neuromodulation regimens in order to successfully treat atleast a portion of patients. For example, Abelson et al (2005) exploredusing bilateral DBS of the anterior limbs of the internal capsule,rather than ablative surgery, for treatment of refractoryobsessive-compulsive disorder (OCD), and found that only two of the fourpatients were aided, while only one of these showed a significantimprovement. In another study, Mayberg et al (2005), investigated DBSfor treatment-resistant depression, and found striking and sustainedimprovement in mood in 4 of the 6 patients, while 2 patients did notobtain benefit of the intervention. These investigators chose theirneuromodulation target based upon positron emission tomography (PET)data which suggested that, in addition to other abnormalities, thesubgenual cingulate region (Brodmann area 25) was metabolicallyoveractive in treatment-resistant depression. Accordingly, treatmentconsisted of modulating this area with DBS to provide inhibitoryelectrical stimulation and decrease this excessive neural activity.While treatment successfully decreased activity in the target area inall patients, this did not lead to improvement of unwanted behavioralsymptoms in 2 of the 6 patients. This suggests treatment will entail amore complicated mechanism than a simple on-off switch for a particularstructure. Further evidence that complex disorders will not alwaysbenefit from simple DBS treatment paradigms comes from Schoenen et al(2005), who attempted treatment of 6 patients with chronic clusterheadaches using DBS of the ipsilateral ventroposterior hypothalamus. Twopatients showed considerable improvement, while 3 patients did not showimprovements and 1 died due to complications during surgery: DBS is nota minor treatment option. Neuromodulation systems and methods cancertainly still benefit from considerable improvement when used for thetreatment of many disorders of the central nervous system.

While these studies each targeted a specific brain region forneuromodulation treatment (although sometimes bilaterally), the imagingdata revealed that stimulation caused modulation of activity in severalareas distal from the site of stimulation: neuromodulation of targetsites affected other areas of brain networks within which the targetsite existed. In the Yianni (2005) study, for example, DBS, (or absenceof DBS) of the globus pallidus showed consistent activation (orhypo-activation) in several brain areas that were distinct from the siteof stimulation. This provides evidence that treatment of a target regionthat is related to a motor disorder may modulate at least 2 or 3 regionsof a brain network, each of which may, or may not, be related to thedisorder. Similarly, Mayberg and colleagues (2005) found changes indownstream limbic and cortical sites (e.g., areas BA10, BA9/46, BA24,BA6, BA40), when stimulation of the target site led to successfultreatment response. Interestingly, both post-treatment responders andnon-responders showed decreased cerebral blood flow in the target neuralregion (Mayberg 2005). Accordingly, differential treatment effects mightbe due to other areas of a brain network being affected by or adaptingto changes in the target brain region.

Support for such network effects has come from neuroimaging data whichhas shown that several brain areas seem to be part of brain networksunderlying different characteristics of major depressive disorder(Bench, 1993; Baker, 1997; Mayberg et al, 2004). Producing a desiredchange in the target area may lead to changes in other areas, at leastunder some conditions, and these other changes can be responsible forside effects, treatment, or treatment resistance. However, these studiesand other prior art do not describe or anticipate methods of improvingtreatment by stimulating multiple areas of the network to compensate forinteractions that may occur between different regions of the network.The prior art has described either stimulating a target location, orstimulating several target locations independently, but does notconsider the role of these targets within a brain network thatcontributes to at least one characteristic of a disorder. There is noconsideration of the influence of the stimulation on other locations ofthe network.

The current invention recognizes, addresses, and utilizes theinteractions and connectivity that exists between different brainregions of a brain network to provide improved treatment. Informationabout interactions between brain structures is used to guide theadjustment of neurostimulation parameters of the treatment protocol. Forexample, linking rules can be used to increase inhibitory stimulation ata first area when stimulation is provided at a second area, wherein thestimulation at second area has shown to produce unwanted increase in theactivity of the first area. Further, network considerations can also beused to guide the evaluation of sensed data. In relation to sensing, thedata sensed from a first brain area can be evaluated differently whenstimulation is occurring in a second brain area, then when it is not.The use of linking rules to guide methods of stimulation and evaluationof sensed data is a novel advantage of the invention. The presentinvention thus provides DBS treatment that adjusts for the activation ofmultiple regions of a network which may or may not be stimulateddirectly. Further, it uses neuromodulation methods that control (e.g.,rebalance) the relative activation levels of different areas of thenetwork. Successful treatment should rely upon neuromodulation protocolsthat take into account (e.g., compensate for) the cascade of effectswhich stimulation of a particular target area may have within the largercontext of the brain networks in which it is a part.

It is an object of the invention to provide neurostimulation of brainnetworks (NBN) by utilizing a stimulation protocol that uses linkingrules to adjust the stimulation provided at one target region accordingto the neurostimulation provided at a different target region, whereboth regions are part of a brain network.

It is another object of the invention to provide a method of treatmentwherein target brain regions are selected and treated based uponcharacteristics of brain networks in which they participate.

It is another object of the invention to provide methods and systems forneuromodulation, control, and responsive neuromodulation which providefor observing, evaluating and utilizing information about the relativeactivity of two or more areas of a brain network to provide treatment.

It is another object of the methods and systems of the invention toprovide NBN to one or more areas based upon the functional or anatomicalconnectivity of two or more areas of a brain network.

It is another object of the invention to independently treat differentsymptoms of the disorder by directed neuromodulation of a brain network.

It is another object of the invention to provide a method ofneuromodulation of several brain areas using a neuromodulation protocolwhich incorporates the fact that these modulate each other, for example,by compensating for connections between brain structures.

It is another object of the invention to provide a method ofneuromodulation of multiple areas of a brain network so that therelative activations, drug levels, or other characteristics arecontrolled in a desired manner.

It is another object of the invention to provide a method ofneuromodulation of multiple areas of a brain network by modulating twoor more brain target regions included in a brain network underlying thedisorder, wherein stimulation in one brain target is modified, at leastin part, based upon stimulation in another of the targets.

It is another object of the invention to provide a method ofneuromodulation of two or more areas of a brain network underlying thedisorder, wherein the activity of at least one brain region is modulatedin relation to the activity sensed for at least a second brain region.

It is another object of the invention to provide a method ofneuromodulation which includes implanting stimulation leads in at leasttwo anatomically distinct brain regions, both of which are involved in anetwork implicated in a disorder, and stimulating these leads tomodulate the network in a desired manner, or to normalize the activityof the network.

It is another object of the invention to provide a method ofneuromodulation which includes treating different characteristics of adisorder by adjusting stimulation in different regions of a network.

It is another object of the invention to provide a method ofneuromodulation which uses linking rules to link the neuromodulationprotocol of one stimulated area to those used at a different modulatedarea.

It is another object of the invention to provide a method ofneuromodulation which comprises alternating between two or more targetbrain regions of a network to deter the emergence of adaptation andneural compensation as may occur, for example, via endogenoushomeostatic mechanisms (e.g., pruning, receptor up-/down-regulation).

It is another object of the invention to provide a method ofneuromodulation of multiple areas of a brain network which includesquantifying the interaction between two elements in a network andcompensating for this during treatment.

It is another object to decrease the risk of unwanted adaptation toneuromodulation treatment by stimulating two or more neural targets of abrain network.

These and other objects will be described and will provide systems andmethods of neuromodulation which will greatly improve treatment ofvarious brain disorders.

BRIEF DESCRIPTION OF THE DRAWINGS

The features and advantages provided by the invention will becomefurther apparent from the detailed description below and theaccompanying drawings, in which:

FIG. 1A shows a preferred embodiment of an implanted brain modulationsystem for providing electrical neuromodulation to two distinct brainregions.

FIG. 1B shows an alternative example of an implanted brain modulationsystem for providing either electrical or drug neuromodulation, or bothto two distinct brain regions.

FIG. 1C shows another alternative embodiment of an implantedneuromodulation system, for providing electrical neuromodulation

FIG. 2A shows a general example flowchart of a preferred method oftreatment of brain disorders.

FIGS. 2B to 2J show examples of flowcharts for alternative methods oftreatment of brain disorders.

FIG. 3A illustrates a network model which does not incorporateinformation about interactions or connections which putatively existbetween two brain structures, or where these in fact do not exist.

FIGS. 3B to 3G show alternative examples of brain network modelscomprised of two or more brain structures, which show the influence thateach structure has on the other as well as the direction, type, andstrength of the influence.

FIG. 4 shows the components of neuromodulation system which can provideneuromodulation of a brain network.

FIG. 5 shows an implanted neuromodulation system, with stimulatorssituated to provide neuromodulation of a brain network.

DETAILED DESCRIPTION

The systems and methods will now be described in greater detail, withreference to detailed illustrative embodiments. It will be apparent thatsystems and methods of the invention may be embodied and modified in avariety of manners without departing from the scope and spirit of thedescription.

The following material provides definitions for terms used in thisapplication. However, these terms may be expanded upon and/or modifiedaccording to the various specific alternative embodiments which will bedescribed.

As used herein, “brain modulation system (BMS)” refers to a system whichprovides neuromodulation of brain networks. The BMS may be realizedusing a “brain neuromodulation device” (BND), for example, an apparatussuch as an implantable neurostimulator, drug pump, or an instrumentwhich provides for both electrical and drug delivery. The BND may be acommercially available generic device which can be adapted toapproximately achieve the intended neuromodulation of a brain network asdescribed herein. A BMS can also utilize a BND which is a transcranialmagnetic stimulator to provide magnetic stimulation. A BMS can berealized completely within a BND, but may also exist in a distributedfashion. For example, the BND may communicate with an external patientprogrammer which can be used to program the BND, and which comprises apart of the BMS. The BMS, and its methods, can include the utilizationof sensed data which is sensed by external instrumentation such as anMRI (magnetic resonance imaging) scanner. BNDs can be implantabledevices, can be partially or completely external, and can be deviceswhich are affixed within the skull.

As used herein, the terms brain—“network”, “pathway”, or “circuit”,refer to two or more brain regions for which at least first brain areahas been shown to modulate at least a second brain area. A brain networkwhich that is identified for treatment would normally contain at leastone brain area that has been associated with a symptom for which therapyis sought. A symptom can be, for example, an undesirable behavioral,emotional, cognitive, brain or sensory process or state. A brain networkcan also be comprised of several divisions (i.e., nuclei, or aspecialized group of cells), within a particular brain structure, suchas the thalamus, since divisions within a structure can modulateactivity in other divisions of that structure, either directly, or via amulti-synaptic pathway. A network can be considered pathological when itis associated with a brain disorder. The pathology can be reflected, forinstance, by sensed data which is evaluated relative to a threshold, orin relation to normal, expected, or desired activity, as may be definedby treatment criteria.

As used herein, “brain disorder” refers to at least one characteristicor symptom of a psychiatric, mood, neurological, movement, epilepsy,behavioral, addiction, attention, consciousness (e.g., coma),psychological, or other central nervous system disorder. The braindisorder can also be a thought processes disorder, memory disorder,“mental disorder”, age-related disorder, cognitive or other disorder ofneural origin. Brain disorders can also include pain disorders,migraine, headache, stroke, and other types of traumatic brain injury.The psychiatric disorders can include, for example, forms of psychosis,anxiety disorders, schizophrenia, and obsessive-compulsive disorder.Rather than being defined by a particular behavior or DSM criteria, abrain disorder may be defined as an abnormality as may be evidenced fromanalysis of neuroimaging data, such as an abnormal EEG or QEEG profile.This abnormal activity may be associated with structures of a relevantnetwork using source analysis methods.

As used herein, the term “neuroimaging” can refer to either functionalor structure neuroimaging. The term “sensing” includes performingsensing using neuroimaging.

As used herein, the term “functional neuroimaging”, refers to any methodwhich provides information about an amount, or changes in amount, ofbrain a characteristic including blood flow, neurotransmitter level,metabolism, electrophysiological activity, and includes informationobtained from either acutely/chronically implanted sensors or externalsources. Functional neuroimaging includes implanted electrodes or othersensors which provide estimates ofneurophysiology/neurochemistry/metabolism or other measure correlatedwith the function of brain regions. Further, functional neuroimaging caninclude techniques such as electroencephalography (EEG) obtained fromeither scalp or implanted electrodes, magnetoencephalography (MEG),evoked-potential (EP), functional magnetic resonance imaging (fMRI), andother magnetic resonance imaging techniques such as magnetic resonancespectroscopy (MRS). Functional neuroimaging includes analysis ofneuroimaging data according to conventional techniques known to thoseskilled in the art. Further, neuroimaging (and collection of self-norms)can occur before, during, and/or after surgery, and can occur when apatient is resting, engaged in a cognitive, emotional and/or other task,and can occur while patients are exposed to medication and/or while drugfree. Neuroimaging may occur using one or more tasks to assess differentsymptoms related to the disorder, for example, one task can pertain tomeasurement of sadness or anxiety, while another can assesshopelessness.

As used herein, the term “structural imaging” refers to any process thatprovides information about the structure of the brain, including MRI anddiffusion tensor imaging (DTI), and CAT-scan, or other methods relatedto function such as SPECT or MRS.

As used herein “treatment protocol” refers to the protocol used by thetreatment program to provide treatment. The treatment protocol hasparameters which define the locations for sensing and stimulatingoperations, and can contain parameter values for the sensing protocol,the stimulation/modulation protocol, and the evaluation protocol. Thetreatment protocol defines the treatment criteria, the reference values,the linking rules, and any other parameter value which is used toprovide specific neuromodulation treatment. A treatment protocol can bedesigned to cause the treatment program to directly modulate regions ofthe brain network, or the regions to be modulated can be modulatedindirectly by stimulation of neural targets in a different area.

As used herein the terms “sensing protocol/parameters” define howsensing is accomplished and can include placement of sensors,measurement of sensed data including when, if, and what data is sensed,and how the sensed data is processed. The sensing protocol determinesthe sensing parameters, for example, sensing rate, type, and location.Sensing protocols, including processing of sensed data, can be guided bylinked rules. Sensing operations are provided by the sensing subsystem.

As used herein the terms “modulation-protocol/parameters” and“stimulation-protocol/parameters” define how stimulating is accomplishedand can include placement of stimulators, stimulation/modulationprotocols including when, if, for how long neural regions arestimulated, and which stimulation signals are used to stimulate one ormore brain regions. The “parameters” refer to the settings used whileachieving the protocol. The stimulation protocol determines thestimulation parameters, for example, stimulation rates, type of one ormore drugs to be delivered, dosage, and location. The stimulationprotocol can be completely predefined or can also include providingmodulation based upon evaluation of sensed data, using data as a controlsignal. Stimulation operations are provided by the stimulationsubsystem.

As used herein the terms “evaluation protocol/parameters” define howsensed data is evaluated. For example, the evaluation protocol definesif the data are compared to reference values such as self-norms,population norms, or selected threshold values. Evaluation of senseddata can be non-statistical, involving simply the utilization of thedata to create a stimulation signal using control laws or filters. Theevaluation protocol selects treatment criterion according to thetreatment protocol, determines how sensed data are compared to referencevalues using treatment criterion, Evaluation operations are normallyprovided by the control subsystem. Further, as used herein, the terms“evaluate the sensed data”, “evaluate treatment”, “data analysis”,“analysis protocol”, can refer to the methods and protocols used analyzethe sensed data. Data analysis can include the step of “processingsensed data” which can refer to signal processing of the sensed data,and processing of the sensed data which converts it into meaningfulunits. “Using sensed data” can entail simple processing of the data. An,example of using sensed data is feeding it through a circuit to create astimulation signal, as may occur using control laws. Evaluating thesensed data can comprise several different types of processingincluding, assessing the sensed data using a criterion which is eithermet or failed, performing a statistical assessment relative to referencevalues stored in the database, using measurements of the sensed data inan equation, model, correlation analysis, or algorithm, which providesresult data.

As used herein the terms “control protocol/parameters” refers to thesubroutine of the treatment protocol that determines what to do if thetreatment criterion is met or not met.

As used herein “reference values” refer to values such as self-norms orpopulation norms, values determined by an equation, fixed values,percentage values, or ratio values.

As used herein, the terms “modulate” and “stimulate” (and hence“neuromodulation” and “neurostimulation”) refer to causing a change inbrain activity, chemistry, or metabolism. The change can refer to anincrease, decrease, or even a change in a pattern of neuronal activity.Neurostimulation may be either excitatory or inhibitory stimulation, andmay be at least electrical, magnetic, optical or chemical, or acombination of two or more of these. When two or more regions arestimulated, one type of stimulation can be excitatory while the other isinhibitory. When used in context of chemical stimulation, the modulationcan include increasing, decreasing, or altering endogenous levels ofneurochemical substances or their metabolism, or rates or amounts oftheir release or reuptake, and can also include dispensing agonists,antagonists, competitive antagonists, precursors and other agents whichmay modulate the function of endogenous substances and processes.

As used herein, the term “stimulation subsystem” refers to allcomponents that permit the BMS to actively alter (‘modulate’) neuraltissue during neuromodulation treatment, and may include at least onepulse generator, drug delivery apparatus, and any circuits or valvesthat permit stimulation to occur in a controlled fashion. Thestimulation subsystem can utilize, for example, electrical or drugstimulation and can also utilize optical stimulation, which may betransmitted into the brain using fiber-optics. The stimulation subsystemcan also rely partially or fully upon external instrumentation such astranscranial magnetic stimulation.

As used herein, the terms “stimulator” refers to any apparatus whichpermits the transfer of at least electrical, pharmaceutical, opticalinfluences or a combination of these from the BND to the target neuraltissue. The stimulation subsystem includes at least one “stimulator” forstimulating at least one brain region. An electrical stimulator may beat least one electrode having at least one contact for providingelectrical stimulation. Using a multiplexer or other method, thiscontact can also be used for sensing electrical activity. When chemical,the stimulator may be at least one catheter having at least one distaltip from which at least one drug may be delivered to accomplishneuromodulation. A stimulator can be an electrical lead originating froma distant source which can provide current pulses or pulse trains, orcan be a self-contained and self-powered local or remotely programmableintegrated needle electrode/stimulator circuit, can be a catheter or acatheter/lead combination. Since any of these combinations can be usedto stimulate target regions, specific embodiments can be understood tobe interchangeable, as is known to those skilled in the art. Stimulatorscan be attached to, communicate with, provide power, and otherwisecooperate with sensors, and can transmit sensed data from the sensorsback to the BND. The “modality” of modulation refers to the type ofstimulation which occurs e.g., drug, optical, TMS, or electrical.

As used herein, the term “sensing subsystem” refers to all sensors andrelated circuitry related to sensing information related to at least onecharacteristic of sensed neural tissue. The sensing subsystem includesat least one sensor.

As used herein, the term “sensors” refers to one or more sensors whichmay be electrical, magnetic, chemical, metabolic, light, biosensor orany other sensor used for detecting, either directly or through atransformation, any activity, structure, metabolism, composition,process related to, or product of sensed neural tissue.

As used herein, the terms “target brain region”, “neural target”, and“target” all refer to a region of the brain which is an intended sitefor modulation.

As used herein, “sensed data” refers to data sensed from at least one ormore electrical, chemical, optical, biosensor, or other type of relevantsensor. Sensed data can be sensed from implanted or external sensors,and instrumentation including functional neuroimaging devices.

As used herein, the term “result data” refers to results of processingand evaluation operations which can be performed on sensed data fromimplanted or external sensors and which may be used to guide or alterneuromodulation therapy.

As used herein, the term “database” refers to a quireiable informationstorage system used by the BMS. Such information can included populationnormative values or self-norm values related to sensed data, which canbe values from prior sensing of the subject, path coefficients relatedto brain network models, linked rules used in performing stimulation.

Network Paradigms for Neuromodulation Treatment

The publication rate for studies exploring current and new techniquesfor neuromodulation of brain disorders is increasing steadily, as arethe number of new clinical trials seeking to approve brain stimulationfor the treatment of these disorders. Additionally, new methods andtechnologies are being developed as evidenced in numerous currentpatents and pending applications. The following are examples whichgenerally describe methods and systems of neurostimulation for thetreatment of various brain disorders which can be adapted to provideneurostimulation as described herein: U.S. Pat. Nos. 5,299,569,5,470,846, 5,263,480, 5,540,734, 6,066,163, 6,061,449, and 6,539,263.While these prior art examples provide a number of useful advantages fortreatment of various disorders, none provide such therapy usingneurostimulation specifically designed for the treatment brain networks.In the treatment of tremor, the therapy can be provided by disruptingactivity, such as hyper-synchrony, in regions of the motor cortex. Inthe treatment of seizures, the therapy can be provided in order todisrupt the emergence of epileptiform activity, and stimulation canoccur in an area where this increased synchrony was detected. In thetreatment of some types of pain, treatment can be provided to blockascending signals so that these do not reach the areas of the brainwhich are responsible for the subjective sensation of pain (e.g.blocking ascending fibers of spinal or thalamo-cortical tracts). Whiletreatment of these disorders may also benefit from network stimulation,sufficient relief can obviously occur when stimulation is designed withrespect to stimulating a specific site, regardless of the state of thenetwork in which it is a part. In contrast, psychiatric and other higherorder disorders of consciousness certainly involve distributed brainnetworks, and relative activation as well as communication betweendifferent nodes of the network underlie various aspects of the disorder,and must be taken into account in order to provide improved treatmentoutcome.

The existence of brain networks, and methods for identifying the brainregions involved in these networks, is well known (e.g., Mcintosh &Lobaugh, 2004; Kong, et al., 2005). Evidence indicates that activationof one area is functionally significant in relation to the state of therest of the network within which that activation takes place. The stateof the network is likely just as important as the activation itself withrespect to the functional role of that. In other words, the functionalrelevance of a brain area depends on the status of other connected areasi.e., the context within which the region is operating. As McIntosh(2004) notes “A region can participate in several behaviors throughvariations in its interactions with other areas”. Studies have exploredthe relationship of these networks to different brain disorders,including disorders of consciousness or with aging, and to loss ofconsciousness during anesthesia, and have demonstrated pathology in theprimary networks of different disorders as well as the existence ofputative compensatory networks (John, 2002; Prichep et al 2002; Stefuraket al, 2003; Mayberg, 2003; Mayberg et al. 2005; Peled, 2004; Gilliam,2004; McIntyre, 2004; John and Prichep 2005; John 2005). However, whilenetworks underlying both normal and pathological functioning, as well asnetworks related to different characteristics of various braindisorders, have been well documented, these have not been incorporatedinto the techniques used to create, or adjust, treatment methods in theemerging field of neuromodulation. The prior art, and current practice,approach stimulation of one or more regions as if these were isolatedstructures, and the operational principle is simply summation: ifstimulation of one area is useful, two might even be more so. Thisstrategy fails to utilize the growing understanding provided by studiesof brain networks, which forms the basis of the methods of the currentinvention.

Evaluating and treating networks using neurostimulation is morepromising than treating individual brain targets. Even when neuroimagingprocedures indicate normal activity levels in regions of a brainnetwork, the communication between two or more nodes of a network may beabnormal. This may be reflected by abnormal covariance (e.g., pathcoefficients) identified by network modeling of sensed data (e.g.,McIntosh, 2004). Accordingly, therapeutic stimulation may strive notonly to increase, decrease, normalize, positively/negatively reinforce,or otherwise modulate the relative activity of different regions of apath or network, but can also be designed to alter the interactionswhich normally exist between these regions. Network interactions mayentail modulation of one area by another, which may be positive,negative or both, due to different fiber tracts or “paths” that join theregions of the brain network, and may also include reciprocalinteractions. Modulations of one area by another may occur directly ormay be mediated by at least one other intervening structure which mayreceive inputs from other regions of the network as well. In oneembodiment, information is utilized about network interactions, and/orneuroanatomical connections, between different regions of the network inorder to identify target structures, set the initial neuromodulationprotocols, and guide the adjustment of neuromodulation protocols duringtreatment. Further, using the concepts of transfer entropy, thecovariance between A & B can be quantitatively decomposed into theeffects of A upon B, the effect of B upon A, and the “mutualinformation” reflecting the common action of some C upon both A & B(Friston et al, 1992, Imas et al, 2005). By using linking rules whichadjust stimulation in one region to that provided in another, basedupon, for example, models of networks the brain network can be treatedrather than just treating isolated regions without adjusting stimulationin relation to the network.

Pending U.S. application Ser. No. 10,872,271, to Lozano et al. (the '271application) describes a method of treating depression, mood disordersand anxiety disorders using neuromodulation. The '271 applicationdescribes treatment using stimulation to modulate “a predetermined site”which may be “a subcallosal area” that includes “subgenual cingulatearea, subcallosal gyrus area, ventral/medial prefrontal cortex area,ventral/medial white matter, Brodmann areas such as 10, 24 or 25”. Theseareas were chosen, in part, due to a number of neuroimaging studiespreviously performed by the inventors of the '271 application whichshowed that these areas were characterized by abnormally high metabolismin depressed patients. A portion of patient data included in the '271application was also included in a study (Mayberg et al, 2005) whichreported that neuromodulation via direct brain inhibitory stimulation ofthe Brodmann 25 area led to successful treatment in 4 of the 6 patients.Generally, the '271 patent teaches stimulating a pre-defined neuraltarget which has been previously implicated in the disorder beingtreated, which in this case was depression. The '271 application furtherdescribes stimulation of several targets which have been linked with adepressive disorder. However, these targets are not recognized as beingengaged in one or more networks which are associated with (e.g., whichcorrelate with) the emergence of symptoms of depression. In the '271application, one or more neural targets are stimulated independentlywithout a consideration of: 1) the relative activity of one area inrelation to other areas of a brain network, and 2) the influence thatstimulation at one site may have on another. Unlike the currentinvention, the interactions or connectivity between two or more regionsof the network, and the effects that stimulation of one target area mayhave on other target, or on non-target, areas of a network, are also notaddressed. Incorporating these network dynamics into the treatmentmethods is a main feature of the current invention. These omissions inthe prior art are addressed by novel features of the methods and systemsdescribed herein, which thereby offer significant advantages over thisart.

Similarly, U.S. application Ser. No. 10/925,519 to Whitehurst, describesmethods of, treating a mood and/or anxiety disorder, by stimulating aseries of structures, however these are identified by review of therelevant medical literature rather than by neuroimaging of the patientsthemselves. In any case, this prior art also does not discuss theexistence or relevance of brain networks or the interactions which canoccur between at least two brain structures that may affect each otherby way of least afferent or efferent fibers.

Pending U.S. Ser. No. 10/072,669, to Tcheng et al, (the '669application) teaches treatment of motor disorders via brain stimulation.While the '669 application notes that stimulation can be applied to “theGPi, thalamus, sub-thalamic nucleus, or any other structure of the basalganglia (or elsewhere in the brain) that provides relief” it does notdiscuss stimulating more than one neural target, or neuromodulation ofone or more networks in which the target brain region is involved. Incontrast, it is stated that “the functional relationships among variousbrain structures are generally not very well understood, and” should notbe used as “a definitive guide to brain activity involved in movement”.In this prior art, neurostimulation simply occurs in response to sensedevents, and the process for choosing, the structure, or structures, tobe stimulated is not described. Further, there is no mention of treatinga disorder by stimulating two or more neural regions of a brain networkunderlying the disorder.

The prior art does not describe tying stimulation parameters used in afirst region to those used to stimulate at least one other region of abrain network underlying a disorder. The prior art does not describetying (i.e. contingently adjusting) stimulation protocols used in afirst region to data sensed in any other regions of a brain networkunderlying a disorder. The prior art does not describe contingentlyadjusting stimulation protocols used in a first region to data sensed inat least two other regions of a brain network, which are modulated bystimulation of the first region, at least one of which underlies asymptom of a disorder. A well known network that would benefit greatlyby this linking strategy are the A9 and A10 structures of the dopaminesystem, wherein therapy intended to differentially modulate treatment ofpsychiatric disorders or movement disorders, may co-occur withdysregulation of the other structure and manifestation of unwantedsymptoms. Lastly, while the prior art also teaches utilizing implantableneuromodulation devices having several leads, each of which may beplaced in a different brain region (e.g., U.S. Pat. No. 6,066,163), itdoes not describe using these multiple leads to modulate two or morebrain regions involved in a pre-defined brain network which has beenassociated with some characteristic of a brain disorder.

Two objectives of brain stimulation are particularly important withrespect to network stimulation methods. The first relates to theendogenous adaptation/compensation which undoubtedly occurs duringpathological development of a patient's brain, and may underlie somebrain disorders. Adaptive changes between two or more nodes of arelevant brain network may be central to treatment, and treatmentrefractoriness, of different disorders (Peled, 2004). While the priorart addresses the issue of adaptation and compensatory modulations ofendogenous activity in response to brain modulation, this issue is notaddressed in relation to networks. Instead, the issue of adaptation toneurostimulation is discussed in relation to local phenomena, withrespect to the specific region being stimulated (e.g. U.S. Pat. No.6,665,562, U.S. application Ser. No. 10/044,405 to Stypulkowski).However, since networks consist of multiple brain areas and therelationships among these areas, influencing one area of a network canlead to adaptation or compensatory responses in other areas of thenetwork (e.g., Eytan, 2003). Accordingly, in line with the currentinvention, stimulation in more than one region of a network will assistin treatment by compensating for adaptation which may occur in a regionof the network. Further, stimulation may be applied to different neuraltargets within a network in order to decrease the risk of adaptationthat may occur when a single area is chronically stimulated over time.The prior art does not describe protocols which alternate stimulationacross brain regions of a network to avoid adaptation of the network tostimulation, or describe adjusting stimulation of one area of a brainnetwork based upon the endogenous or modulated activity of a differentarea of the network.

The second is treatment selection. Since different brain networks havebeen shown to be predictive of drug response with respect to drug type,independent of similar overt behavioral and mood characteristics,detection of pathological networks can determine two or more targetareas for which NBN may be most effective. Imaging data derived from,for example, PET or scalp electrodes have shown to reflect networkactivity that accurately predicts response to treatment (John, 1994;Seminowicz, 2004). Accordingly, in line with the current invention, twoor more neural targets can be selected for treatment based upon analysisof imaging data, for example characteristics of modeled brain networksof a patient suffering from a brain disorder. Further, the stimulationprotocols can be chosen based upon the characteristics of two or moreregions of the network, determined from sensed data which is analyzedusing a network model or other appropriate methods. Additionally,parameters and brain targets can be chosen based upon the similarity ofa new patient's brain activity, and brain network model, with those ofprevious patients who have been successfully treated with certainprotocols. Having described the general goals of the systems and methodsof the invention, specific embodiments will now be described in anenabling fashion.

Neuromodulation System Embodiments.

FIGS. 1 a, 1 b and 1 c illustrate examples of brain neuromodulationdevices 10 a-c, which can be used to provide neuromodulation of brainnetworks in the treatment of various brain disorders. Considerablepending and prior art describing implantable neurostimulation and drugdelivery systems share features of the BND, and are commonly known bythose skilled in the art. For example, U.S. 20030149457 contains aneurostimulation device which could be utilized to achieveneuromodulation of a brain network. It contains a stimulation subsystemhaving both electrodes for providing electrical neuromodulationaccording to a stimulation protocol and also a drug dispenser forproviding pharmaceutical stimulation. It contains a computer subsystemwith memory, a CPU, a real-time clock, communication subsystem forcommunicating with external equipment such as a patient programmer via,for example, telemetry, and a power supply. The computer subsystem alsocontains circuitry to perform signal processing and statistics on thesensed data in order to guide therapy. Its components operate to providesensing from implanted sensors and processing of the sensed data todeliver either electrical or pharmaceutical treatment. Other examples ofimplantable neurostimulators are U.S. Pat. Nos. 6,066,163; 6,597,954,6,051,017; 6,735,474; 6,735,475; and U.S. application Nos. 20030204226,20030135248, all of which could be utilized to provide modulation ofbrain networks by adjusting their treatment programs so that they occuraccording to the methods of the present invention.

FIG. 1 a shows an embodiment of the invention where an implantable BND10 a is an electrical deep brain stimulator such as the Aptiva™ producedby Medtronic. The device 10 a has a connector component 12 a to whichone or more leads 14 a, 14 b can be connected. The leads 14 a, 14 b eachhave one or more electrical contacts 18 a, 18 b which are placed tostimulate the target areas of the brain network according to stimulationprotocols. The contacts 18 a, 18 b can also serve as sensors which sensethe endogenous electrical potentials. The control subsystem 34 canpermit some contacts 18 a to sense data from target brain regions whileother contacts, 18 b simultaneously stimulate target brain regions. Forexample, using a multiplexer, each of the electrode contacts can beoperationally connected to a stimulation subsystem or a sensingsubsystem of the device 10 a. Although the leads 14 a, 14 b each containat least one electrode contact, preferably a plurality of independentlyoperable electrode contacts are provided.

FIG. 1 b shows an alternative embodiment, where an implantable BND 10 bis a drug pump containing at least one drug to be dispensed duringneuromodulation treatment. The device 10 b has a connector component 12b to which one or more catheters 16 a, 16 b can be removably, orpermanently, connected. Each catheter tip is implanted to deliver drugto a target brain region which is part of at least one brain network.The catheters 16 a, 16 b may also have at least one distal component 20which is electrically connected to the device 10 b, so that, in thisembodiment, the stimulator provides both electrical and chemicalneuromodulation. The distal component 20 can be an electrical contact toprovide electrical sensing/stimulation of the target, so that the device10 b can provide both electrical and drug neuromodulation. The distalcomponent 20 can be an optical sensor or stimulator to provide opticalsensing/stimulation for the target, so that the device 10 b can utilizeoptical neuromodulation and optical sensing. The distal component 20 mayalso be at least one chemical sensor, optical sensor, electrical sensor,biosensor, or other sensor for sensing a characteristic of the targetarea. The distal component 20, may also be a valve which is controlledby the control subsystem 34 in order to control release of drug, or thevalves may be located more proximally, for example, the connectorcomponent 12 b can contain a programmable valve structure. The treatmentprogram of the control subsystem can instruct for the operation of thesevalves to provide differential pharmacological modulation of the targetbrain regions of the brain network according to stimulation protocols ofthe neuromodulation device 10 b. In most embodiments, the BMS utilizesone or more implantable drug delivery devices which have activecomponents for controlling, for example, rate, amount, and type of drugto be delivered as part of therapy. However, passive drug pumps can alsobe used. If passive pumps are used, then the drug delivery parametersmay be set independently, but according to linking rules, to providedrugs to two or more targets in the treatment of the brain network.Lastly, passive pumps can be used with active accessories (e.g., U.S.Pat. No. 6,880,564 entitled “Dosage control apparatus”), which can beused to control the rate and location of drug delivery within thenetwork being treated.

FIG. 1 c illustrates yet a further embodiment of the invention where animplantable brain neuromodulation device 10 c is an electrical deepbrain stimulator having a connector component 12 c to which only oneelectrode lead 14 c is connected. The lead 14 c has two series ofelectrical contacts 18 c, 18 b to stimulate the first and second targetbrain regions of the brain network according to neurostimulationprotocols of the BND 10 c. For example, a brain structure may bestimulated by 18 c and its efferents may be stimulated by 18 d, in orderto desynchronize their firing, so that stimulation of this structure canoccur without resulting in unintentional modulation of a second brainregion in another part of the network. Similar to 18 a and 18 b, theseries of contacts 18 c, 18 d can also serve as sensors.

FIG. 4 illustrates the functional components of the BND 10 d whichincludes a sensing subsystem 32 which controls sensing operations andcommunicates with sensors, a stimulation subsystem 30 which controlsstimulating operations and communicates with stimulators, and a controlsubsystem 34, which communicates with and controls the sensing subsystem32 and the stimulation subsystem 30. When the BND 10 d, provides drugtherapy the stimulation subsystem 30 contains an active or passivemechanism for biasing the flow of a drug contained in a reservoir sothat it is dispensed approximately in an intended manner. The controlsubsystem 34 contains a rechargeable power source, processor, memory,real-time clock, and communication means to achieve the controlprocesses provided for in implantable BMDs as are well known anddescribed within the cited prior art. The processor 36 may be realizedas a computer subsystem with processing circuitry which resides withinthe controller subsystem and which communicates with the sensing and/orstimulation subsystems. Such communication may be accomplished by meansof an information transmission system which includes telemetry means.The processor can processes sensed data to produce result data, which isthen used to determine if, and what type of, neuromodulation is needed.The computer subsystem also contains hardware for processing the senseddata by at least filtering, amplification/attenuation, A/Dtransformation, correlation, modeling, signal processing, andregistration. The computer subsystem also permits the BMS to initiate ormodify neuromodulation based upon for example, pre-defined protocols,user input from an external controller, sensed data, result data, ortime of a real-time clock. The BMS can communicate with the processors36 of one or more implanted BNDs to coordinate neuromodulation of brainnetworks. It should be noted that in conceivable circumstances, such asa multi-bed intensive care unit or coma ward, there might be a centralstation that remotely communicates with the processors of multiple BNDswhich are treating multiple patients.

A processor 36, which can be provided with programmable code, orcircuitry for achieving the functions of this code, provides thetreatment program of the BND 10 d with the ability to evaluate thesensed data using signal processing algorithms and/or modeling, and tocompare the sensed data to treatment criteria. Treatment criteria definenormal or desirable values and ranges for the sensed data. When senseddata meet treatment criteria (e.g., restore abnormal values to desiredlevels such as within a normative range), then the criteria beingevaluated, for those region(s) of the brain network being evaluated, aremet. Often, when criteria are met the modulation parameters are notchanged. When the sensed data fail to meet treatment criteria, thenstimulation must usually be either initiated or adjusted. Alternatively,the treatment protocol may dictate that a treatment criterion must failto be met a number of times, or for a specified duration, or to aspecified degree, before The evaluation protocol defines the treatmentcriterion as not being met. This may occur by storing a history ofcomparison results, sensed data, or summaries of sensed data in thedatabase 38, and the control subsystem 34 can evaluate this history, forexample, by comparing it to treatment criteria related to number ofevents of duration of the events, self-norms or trends. The treatmentprogram can contain a control protocol which directs the controlsubsystem to control the treatment according to whether the treatmentcriteria are met or not, in relation to linked rules. For example, thecriteria can require that data sensed from two nodes of a network eachmeet specified criteria, which may be set in relation to each other. Thetreatment criteria can be selected by the control subsystem 34 from thedatabase 38. The database 38 can store values related to the sensed dataand can contain self-norms, population norms, linking rules, and otherinformation and reference values utilized by the control subsystemduring the sensing, stimulation, and evaluation processes carried out toprovide the intended neuromodulation of the brain network. Thehistorical records of sensed data itself and transformations andsummaries of the sensed data, can also be kept in the database of theBMS. The database can store normative values of, for example, relativeactivity levels between structures. The database can also storestimulation protocols, including protocols to deter adaptation by thenetwork to treatment stimulation which include, alternating differentparts of the network. Adaptation-related stimulation protocols can bespecifically triggered when adaptation, such as network adaptation, isdetected by the BMS.

FIG. 5 shows an embodiment of the BMS where a BND 10 d is implanted in apatient in order to provide stimulation to two regions of a brainnetwork underlying a disorder. In this embodiment the BND 10 d has alead 14 a which has a set of two electrical contacts 18 a which provideelectrical stimulation to a first neural target Nt1, and a catheter 16a, which provides drug modulation of second neural target Nt2. Theelectrical contacts 18 a, and the distal component 20 of the cathetercan provide both electrical stimulation and sensing.

Methods for Neuromodulation of Brain Networks.

FIG. 2A illustrates an example of a method for neuromodulation of brainnetworks in the treatment of brain disorders. First, a patient isidentified 100 as having a brain disorder and also as appropriate fortreatment. One or more candidate brain networks which are related to theunwanted symptoms of the disorder are then identified 102 fromneuroimaging data. The BND is implanted 104 so that at least one brainnetwork may be stimulated. Modulation of the brain network 106 thenoccurs in the treatment of the brain disorder. For example, stimulationmay occur in two regions in order to compensate for interactions betweenthose regions, and this can occur using linked stimulation rules as willbe discussed. In the next step, the effects of the treatment provided bythe modulation of the brain network are evaluated 108, and eithermodulation is then repeated 106 without adjusting the parameters, ormodulation parameters are adjusted 110, and then modulation 106 againoccurs. When neuroimaging data is obtained and treatment is evaluated108 the data can be compared to reference data using treatment criteria.This comparison may result in either a positive result whereinmodulation parameters are adjusted 110, or a negative result whereinmodulation parameters are not adjusted, and then stimulation is repeated106. Alternatively, evaluation of the treatment is not necessary on aregular basis, and neuromodulation treatment simply consists of steps100 to 106, wherein modulation of at least two areas of a brain networkoccurs using a stimulation protocol which utilizes linking rules.

With respect to patient identification 100, appropriate patientidentification may be based upon a number of criteria selected by themedical experts providing treatment. For example, patients who have beenrefractory to various medications over a sustained period are obviouslyprime candidates, as are patients who suffer disorders for whichmedication is not helpful (e.g., traumatic brain injury). Patients canbe selected based upon medical history, psychological orneuropsychological testing, neuroimaging data collected from internalsensors such as acutely implanted electrodes, or external sensors, suchas the results of structural, and/or functional neuroimaging tests.Patients who demonstrate certain profiles of test results can becompared to profiles of previous patients who either did, or did not,respond well to neuromodulation treatment. In the latter case, thecandidate patient may not be selected as appropriate for therapy.

With respect to identification of brain networks 102 which will bemodulated during treatment, in one embodiment, sensed regions, targetregions and neuromodulation parameters for treatment may be choseneither based upon the knowledge gained from the patient or frompopulation data. The data can include models of the putative brainnetworks responsible for a particular brain disorder and appropriatetargets of the network can be identified prior to surgery. A comparisonof a model of the patient's brain networks to models of networks ofprior patients for whom treatment was successful can assist in designingthe therapy, including selecting treatment sites for sensing andstimulation according to the similarity of a patient's profile withprofiles of past patients. For example, in one NBN treatment method apatient can be classified into one of a number of existing sub-groupsusing discriminant or cluster analysis of measures of the network, ortransformed measures (e.g., z-transformed, factor scores, modelcoefficients). Generally, this method includes the steps of obtainingtest results such as neuroimaging data for a patient, making acomparison of the test results of the current patient to past testresults of patients who were successfully treated using a particularneuromodulation treatment protocol, classifying the current patientbased upon this comparison, selecting a treatment paradigm based uponthis classification. Additionally, the one or more targets of a brainnetwork which are chosen for treatment may include structures which havebeen shown to have functional or structure interaction, for example, dueto afferent or efferent pathways which connect the two or morestructures, either directly or via at least one intermediary structure,and which are related to the pathological condition. Further,sensed/target regions and neuromodulation protocols may be chosen basedupon imaging of a subject's brain, using some of the examples related toidentification of brain networks which are provided in the sectionentitled identification of brain networks.

In steps 100 through 108, functional imaging data may used to identifyand evaluate the brain networks of a patient before and duringtreatment. Although the BND can sense data and evaluates this data toguide treatment, the steps of the method of FIG. 2A can occur in anon-automatic fashion under the direction of a physician. During any ofthe steps of the method, neuroimaging data can be obtained for a subjectduring one or more conditions including, baseline conditions, (forexample, during rest eyes-open, during rest eyes-closed), or duringactivation while engaged in at least an emotional task, a sensory task,a memory task, a stressor task, cognitive task, target detection task orother type of task which may activate the brain network underlying acharacteristic of the brain disorder, or by comparing the resting andactivated states. Imaging data may also be obtained for a subject whilethe subject is presented with stimuli to which a response may, or maynot, be required, or using stimuli which have a low or high emotionalaspect (e.g., faces with different expressions, unpleasant or disturbingimages), or during activation with cues related to a disorder, such asdisplaying drug paraphernalia to a person with substance abuse disorderor phobic objects to one with a phobia. Subjects may also be asked tointernally generate stimuli (e.g., think of an unpleasant experience).Imaging data may also be collected while the patient is exposed to atreatment medication, a substance which may acutely modify or worsen thebrain disorder, or a substance which will alter brain activity ormetabolism in a useful manner with respect to gaining information aboutthe brain network underlying a characteristic of the disorder. Imagingdata across conditions can be manipulated (e.g., subtracting a baselinecondition from a task condition), processed, and analyzed using numeroustechniques described in the literature. The results can then be used toobtain information related to the brain networks, can be used to assistin determining the placement of the sensors and stimulators, and can beused to adjust both initial as well as subsequent parameters forneuromodulation.

Generally, by measuring the amount of abnormal activity, functionalimaging data can be used to quantify the disease state and changes inthis state that occur during the treatment of the disorder. Rather thanoccurring within the BND itself, under the direction of a physician,abnormal activity in dispersed portions of a network may be measured ina number of manners, for example, by superposition of three dimensionalsource localization of the generators of quantitative EEG (QEEG)measurements. The characteristics of sources waveforms (e.g., coherence,band-limited power) can be referenced to either population or“self-norms”. By “self-norms” is meant a set of parameters derived froma reference state of the patient, for example, prior to the onset of aBMS intervention. A number of well performing QEEG source localizationmethods are currently available such as, for instance, Low ResolutionElectromagnetic Tomographic Analysis, also known as LORETA(Pascal-Marqui et al). The sources may be constrained by either MRI'spreviously obtained from the individual patient or slices from aProbabilistic MRI atlas such as that provided by Evans et al. The use ofQEEG imaging provides the advantage of confirmed normative data forregional brain electrical activity which is not yet available for otherneuroimaging methods. The current sensed data can occur interleaved withintervals of brain stimulation in order to avoid the issue of electricalartifact with respect to evaluation of sensed data, especially when theneurostimulation occurs in a frequency range that is within the bands ofpower being measured.

Using data about one or more brain networks of the patient and someaspect of the patient's disorder, the relationship between these can beestablished by imaging techniques such as path/PLS analysis and SEM ortransfer entropy computations. Targets for neurostimulation, andcandidate neurostimulation parameters, can be determined due to aspectsof the model analyzed using methods such as correlation of hyper-(orhypo-) activation with some aspect of the disorder, absolute or relativeactivation, connectivity (path) coefficients, directionality ofinfluences within a network, latency differences between activation ofdifferent regions, etc. Alternatively, locations for neurostimulationand the initial stimulation parameters can be determined by any othercriteria, such as a neurosurgeon's experience, neuropsychological tests,or other means.

With respect to implantation of brain modulation system 104, eitherframe or frameless techniques may be used to ensure that stimulators areimplanted correctly to modulate the intended targets. As is well known,if frameless techniques are used, then the imaging data is used to makea 3-dimensional virtual map which is fit to the stereotaxic frame ofreference in the surgical field using reference points located on thepatient's skull. There are many instruments for frameless image-guidedsurgery which can assist the neurosurgeon in determining accurateplacement of the neuromodulation leads and/or catheters with respect tothe intended neural targets (e.g., Stryker Navigation Neuro Module). Inone embodiment of the method, if a stimulation electrode is configuredas in FIG. 1 c, then one section e.g., 18 c, can be implanted tostimulate a first target area of a brain network, and a second sectione.g., 18 d can be situated in a nearby structure or an afferent orefferent fiber tract, so that the target structure can be stimulated inone manner, while its projections are stimulated in another manner. Forexample, if the activity of the target region is to be stimulated in aninhibitory fashion, but the afferent pathway leads to a structure whichshould not be affected, then the second section 18 d can be stimulatedin a fashion that disrupts, blocks or otherwise counteracts the effectsof the signals which would normally travel along that pathway therebycreating a functional lesion that can be reversible or intermittent ifsuch might be advantageous. Step 104, can consist simply of implantingat least 2 stimulators in a brain network.

In one method of providing NBN treatment the neurosurgical procedureoccurs as follows. First at least a first sensor or stimulationelectrode is placed in one neural target of a brain network and a secondsensor or stimulation electrode is place in a second neural target of abrain network. Secondly, different stimulation protocols can beevaluated in order to determine the effects of the neuromodulation onthe network. Thirdly, locations are chosen which produced not only theintended stimulation of target structures, but also either beneficialinteractions between structures or interactions which could be counteredby stimulation using linking rules. The evaluation of neuromodulationprotocols and sites of stimulation can be accomplished with the activeparticipation of the patient, whereby the patient provides self-reportsfor different mood, cognitive, or behavioral rating scales. The patientmay also be given drugs or exposed to stimuli which cause changes in thetarget brain network that are informative about the efficacy of theneuromodulation treatment. If a model of the brain network has beengenerated for this patient, and the model dictates that certain amountsor types of activity should occur in different regions in order toprovide treatment, then the stimulation protocol, including sites ofstimulation, may be changed until these target values are evidenced bysensed data.

With respect to modulation of brain networks 106, during thepost-surgical treatment of the disorder, the BMS must be programmed andthe effects of neurostimulation assessed. BMS neuromodulation treatmentprotocols can be adjusted by patients or doctors, using an externalpatient programmer, to modulate the brain network in order to achieveand optimize therapeutic efficacy. Treatment protocols can also beadjusted based upon data sensed by the implanted sensors, according torules used by the BMS.

In one embodiment, neurostimulation parameters can be set by the medicalpersonnel based upon the results of functional imaging. Theneuromodulation parameters can be adjusted until the target regions aremodulated in a desired manner. For example, activity in regions of thenetwork is increased, decreased, or otherwise altered. The results ofthe functional imaging can be analyzed using path analysis or otheranalysis which provide a model of the neural network being modulated,and the neuromodulation protocol can be iteratively adjusted until, forexample, the model indicates normalization, in other words, that acharacteristic of the brain network more closely approximates that foundin normal control subject or is otherwise maintained within a specifiedrange.

Neuromodulation treatment can occur continuously, periodically, inresponse to patient demand, or responsively due to evaluation of senseddata. Additionally, a first protocol can be used for continuous orperiodic neuromodulation, while a second protocol which is used inresponse to patient demand, or in response to evaluation of sensed data,is interspersed with or is used in combination with the first protocol.

With respect to evaluating treatment of the brain networks 108,evaluation can occur by comparing sensed data to reference data, whichcan be normative data, with respect to treatment criteria. Treatmentfailure may occur when brain activity of certain regions in thepatient's brain deviate from the normative goals embodied by thetreatment criteria, and treatment success may be judged by the return ofthe deviant features to within the normative range. Such change can bequantified by representing the patient's brain state as a multivariatevector (Brain State Vector, or BSV), in a multi-dimensional signal spaceand using the length of the BSV to quantify the distance from thenormative region centered around the origin of the signal space. The BSVcan be a vector computed as the difference between normative vector andan abnormal vector, or alternatively the BSV can be computed fromz-scores and thus can be both statistically-based and normalized.Effective treatments should shorten the BSV, incorrect treatment maylengthen the BSV, and “side effects” may cause a change or rotation inthe direction of the BSV in the signal space. The BSV can be computedupon the components of network model (e.g. SEM) wherein selectedcomponents best reflect the state of the disorder being treated. Inother words, abnormal activity of the network is normalized or changedto bring an undesirable characteristic of the network closer to adesired level.

In one embodiment, if the desired changes are not reflected in eitherthe subjective experience of the patient, or the data sensed by theimplanted sensors, then the neural target area can be changed or anadditional neuromodulation target may be chosen. However, it should benoted that alterations of neural firing patterns and adjustments inneurotransmitter and receptor systems which may play important roles inthe therapeutic effects of brain stimulation, may have slow timecourses, evolving over days or weeks, and accordingly evaluation may notbe possible during a single surgical session. In other words,stimulation may not immediately manifest therapeutic benefit. Further,initial parameters may have to be altered should adaptation occur asneurostimulation continues over time. At the end of the surgicalprocedure, or during a follow-up session which occurs at a later time,surgical closure occurs with the various components of the brainneuromodulation system being adjusted and secured within the patient, sothat surgical recovery can be initiated.

Evaluation of sensed data may indicate that stimulation of two or moreregions of a brain network does not meet a treatment criterion. Atreatment criterion can be, for example, that some characteristic ofneural activity (e.g., power in a certain frequency band,neurotransmitter levels) must remain above or below, a specified value.For example, evaluation of sensed data may indicate that stimulation ofa neural target may not have reached treatment criteria for one or moreregions of a brain network. One type of evaluation of sensed data whichcould cause a change an existing, and/or evoke an additional,neuromodulation protocol, is a “network event”. An example of a networkevent is when two or more regions of a network fail a treatmentcriterion with respect to each other. For example, a treatment criterionmay state that brain region 1 must demonstrate an average value of acharacteristic which is X % above that of brain region 2 (e.g., Brodmannarea 25 must have 15% lower activity levels than Brodmann area 10).Network events occur when sensed data indicates that the neuromodulationtreatment has failed to produce the desired modulation in at least onecharacteristic (e.g., activity level, correlation,) between 2 areas of abrain network. Network events can be constrained by conditional ruleswhich govern the evaluation of sensed data. For example, a conditionalrule may state that a network event must occur for at least a specifiedduration before a criterion is considered to have been passed or notmet. The treatment criteria used to evaluate sensed data with respect tonetwork events can utilize simple thresholds, statistical criteria,population or self-norm data, and may rely upon the output of modelingalgorithms which compare the results of the modeling of current data totarget values for the model, to see if the treatment criteria have beenmet. The detection of network events can occur due to the evaluation ofsensed data using treatment criteria and can occur automatically in theprocessor of the control subsystem of the BND.

The reinforced firing pattern can either be intracellular, obtained frommicro-tipped electrodes, or can be ensemble activity (spikes) asrecorded in local field potentials (LFP), with the band width and gainof the sensing amplifiers set accordingly. When micro-electrodes areused, then the reinforced firing patterns can be based upon post-timehistograms (PSHs) or identified patterns of spikes, where time zero forthe PSH at NtB is determined by (time-locked to) stimulation at NtA.This level of firing pattern analysis within the-BMS is computationallyhigh. A computationally less complex manner of examining the response ofNtB to stimulation at NtA is to compute the time-locked narrow-bandspectra of the activity recorded at NtA, where an increase in a certainfiring pattern will result in an increased spectral power in respectivebands, or will have a specific signature detected by time-frequencyand/or wavelet analysis (wavelet packet or complex wavelet analysis).

Sensed data can relate, for example, to at least dopamine, serotonin,GABA or other neurotransmitter level, chemical or electrical activity ofa neural population or group of cells, a neurotransmitter metabolitelevel, a medication or drug level, a hormone level, a blood-bornesubstance level. Sensed data can also relate to the relative levels ofone or more measurements made, either within, across, or between brainregions, or can relate to a change in these levels over time.

Generally, the method of FIG. 2A solves a problem of prior art whichteaches neuromodulation for treatment of various brain disorders as ifthese each are due to a single area of abnormal activity, which is notpart of a network. The methods of FIGS. 2 a-i are primarily designedwith a consideration of the indirect changes which connections betweenthe nodes of the network produce due to stimulation of these nodes. TheNBN methods of FIGS. 2 a-i also address the fact that disorders areusually not constrained to a single unwanted characteristic. Multipleunwanted features often characterize a single brain disorder, sometimessimultaneously, but also not, and also to varying degrees. Accordingly,stimulation of a network should differentially treat characteristics ofa disorder by specifically modulating areas of the brain that primarilydifferent characteristic of a disorder. In the case of depression, thedifferent characteristics may be sadness, hopelessness, anxiety,antipathy, frustration, indifference, helplessness, or lethargy.Although there is obviously not a one-to-one mapping of these featuresof the disorder with brain structures, the idea is that stimulation totreat one area should compensate for the effects of this modulation onother areas so that other features are not unintentionally augmented.Characteristics of other disorders for which treatment is sought may be,for example, obsession, compulsion, inattentiveness, hyperactivity, andmemory deficits whether recent, short term or episodic. Generally,methods for treating patients with a brain disorder comprisesneuromodulation of at least 2 regions of a brain network, one of whichhas been at least partially associated with an unwanted characteristicof a brain disorder. While a particular region is being stimulated, theother brain regions are modulated in relation to the stimulation of thisregion. In this way, the successful treatment of one characteristic of adisorder will not cause changes in a different characteristic, as a sideeffect of treatment.

In another embodiment, a method of neuromodulation of a brain networkfor the treatment of a brain disorder includes providing stimulation toa target brain region of the brain network according to a stimulationprotocol that produces neuromodulation of the target area as well asmodulation of a second brain area of a network, the second area beingsufficiently distal from said stimulation that it is not directlymodulated by said stimulation 120, (of FIG. 2B). The method may only bestep 120, or may also comprise sensing data and adjusting theneurostimulation protocol. These additional steps can include sensingdata from at least regions 1 and 2 122, evaluating the sensed data usingtreatment criteria 124, adjusting said stimulation protocol if one ormore of the treatment criteria fail to be met 130, such as the measureof activity in the first and second brain regions being within aspecified range, and then repeating stimulation. The treatment in FIG.2B lower, is for a continuous stimulation protocol. Of course, thisprotocol can be made responsive by including the subroutine within thedashed lines, which contains steps 122 b-128 b, wherein stimulation isnot initiated until evaluation of sensed data indicates 124 b this isnecessary 128 b. It is obvious that this routine, or a similar routinecan be easily appended to the other methods described herein and shownin other figures. In another embodiment, illustrated in FIG. 2C a firststimulation protocol can be used for stimulating a target region of abrain network (e.g., C in FIG. 3G) 132 a so that a desired change alsooccurs in a second region of the network (e.g., A in FIG. 3G). Step 132a can comprise the entire method, where the stimulation protocol isdesigned to stimulate not only the neural target, but also a secondaryarea of the brain network, in a desired manner. Additionally step 132 acan be incorporated into a feedback method, where data is sensed 134 aby a sensor in a second neural target in order to adjust the stimulationprotocol according to steps 136-142. Further, a second stimulationprotocol can be used to modulate the same target region 132 b in orderto provide a desired change a third region of the network (e.g., B inFIG. 3G), said change being sensed 134 b, and the stimulation parametersbeing changed if dictated from evaluating the sensed data 144 a. Step144 includes the subroutine that is comprised of the steps locatedwithin the dashed area of the figure, the notation being evaluate thesensed data (EV) & compare (CO) to treatment critera2 (TC2) and adjuststimulation protocol #2 (ASP2) if needed. The portion of the stimulationprotocol on the left side of FIG. 2C may be combined with thestimulation protocol illustrated in FIG. 2D, wherein a different changeoccurs in the second brain region of the network due to steps 132 c, 134c, and 144 b. The stimulation protocol used at one part of the networkcan be adjusted to differentially stimulate other parts of the networksince different stimulation parameters will modulate different subgroupsof neurons within the target area, which consequently providedifferential modulation of other parts of the network. The adjustment ofstimulation protocols in one region, based upon the effects ofstimulation at a target area on other parts of the network is novel overprior art which has largely ignored secondary effects of stimulation(e.g., the fact that specific regions of a network can modulate activityin other regions). By stimulating at least one brain region of a networkand sensing data from other parts of the network located relativelydistal from the field of stimulation, the stimulation can be adjusted(e.g., through trial and error or based upon a network model) to producethe desired secondary effects (or additional stimulation can be providedto counter secondary modulation of these other areas).

In another embodiment, neurostimulation can occur in response to sensedmedical events. A medical event can be detected, for example, using atemplate matching strategy or algorithm which can produce a probabilityscore that an event has occurred, where when the probability score isabove a specified threshold the event is considered to have occurred.Alternatively, the medical event algorithm can simply provide atrue/false indicated that the event has occurred. The medical event canbe, for example, a seizure, a network state, the approximatelysimultaneous drop in activity at a number of sensors which indicates achange in the network state. In this case, the absence of a medicalevent is evaluated as meeting a treatment criterion, and the detectionof a medical event is evaluated as the failure to meet a treatmentcriterion. For example, if stimulation was occurring before the medicalevent occurred, detection of the medical event can lead to a change inthe stimulation protocol, or the addition of a responsive stimulationprotocol. Alternatively, if stimulation does not occur continuously (orat least periodically), then detection of a sensed medical event cancause stimulation to occur. When stimulation is initiated, this canoccur at two or more areas of the brain network, and can be guided bylinking rules.

In another embodiment, an example of which is illustrated in FIG. 2E,neurostimulation of the network is provided in order to either increaseor decrease the connectivity of the network by training using a Hebbianstrategy. For example, stimulation can occur according to a protocol 1at neural target A (“NtA”) 150, while data is sensed at neural target B(“NtB”) 152. When stimulation of NtA leads to increased activation ofNtB (i.e. the activation occurs rapidly enough at NtB that it is likelydue to activation of NtA) as defined by a criteria 156 then theneurostimulator stimulates according to stimulation protocol 2 158,which in this case is stimulating NtB in order to increase the synapticconnectivity. If the treatment criteria fails 159, then stimulation ofbrain region 1 150 again occurs, after adjustment if indicated. Further,stimulation of an area can be used to reinforce a particular type offiring pattern in the neurons of that area. In one method, an example ofwhich is shown in FIG. 2F, a sensor is located in both NtA and NtB, andsensed data is obtained from both regions 160. Select a reinforcedfiring pattern 162, which can occur in several manners as is known tothose skilled in the art Various schedules of reinforcement can beimplemented, including aperiodic, contingent, etc. In one method, ahistogram can be generated wherein, for example, the counts for each ofthe different classes of neural firing patterns in NtA are added to thehistogram whenever the firing pattern in NtA is followed by an increasein activation (or a desired firing pattern) in NtB. The class ofneuronal firing in NtA which is most likely to provoke a change infiring in NtB will have a higher count in the histogram than other typesof firing patterns which do not evoke changes in NtB, and this firing isthe “reinforced firing pattern”. Accordingly, treatment criteria 1, actsto reinforce the firing pattern when it occurs 166, by stimulating NtBaccording to stimulation protocol 2 168 whenever the pattern to bereinforced occurs at NtA, where providing stimulation protocol 2 168consists of stimulating area NtB to strengthen this association.Alternatively, stimulation protocol 2 168 can be stimulation of NtAwhich occurs to reward and reinforce the occurrence of this desiredfiring pattern. In this manner the strength of the connectivity of atleast 2 regions of the network can be strengthened. This type ofreinforcement is intended to ‘retrain’ a part of a brain network and canlead to a decreased need for subsequent stimulation therapy.

Identification of Brain Networks and Adjusting Stimulation Parameters.

The identification of numerous brain networks which putatively underlie(i.e., correlate with symptoms of) various brain disorders has come frommany areas of neuroscience. Anatomical studies utilizing animal orpost-mortem brains, or structural imaging, including computerizedtomography (CT), magnetic resonance imaging (MRI), and its variants suchas diffusion tensor imaging (DTI), have provided direct and indirectevidence of the role of brain networks, and the individual brain regionsof these networks, in normal functioning as well as in various braindisorders. Functional imaging techniques which are accomplished withexternal sensor or techniques with use acutely or chronically implantedelectrodes or neurochemical sensors, and pharmaceutical manipulationshave all provided valuable data related to the metabolism, activity,connectivity, and neurochemistry of these brain networks. The targets ofthe network to be used for neuromodulation treatment can be identifiedfrom the results of these previous studies, functional neuroimaging ofthe patient's brain, or a combination of the two. Prior studies whichcan be used for identifying brain networks related to pathologicalaffect, can include studies where healthy volunteers were asked toexperience an emotion (e.g., sadness, anxiety).

There are many recent imaging studies which have identified brainnetworks underlying various disorders. In a series of studies, Northoff,and colleagues (2000, 2002, 2004) have used both fMRI and MEG toinvestigate brain networks for disorders such as Catatonia (apsychomotor syndrome characterized by concurrent emotional, behavioral,and motor abnormalities), and brain networks related with positive andnegative emotions. With respect to Catatonia, pathophysiologicalmechanisms related to abnormal emotional-motor processing were examinedin prefrontal cortical networks, while subject viewed pictures havingpositive or negative valence. Catatonic patients showed alterations intheir orbitofrontal cortical activation pattern and also in functionalconnectivity to the premotor cortex in both negative and positiveemotions, compared to psychiatric and healthy controls. Catatonicbehavioral and affective symptoms correlated significantly withorbitofrontal activity, whereas catatonic motor symptoms were ratherrelated to medial prefrontal activity. While imaging data may have shownabnormal activation in specific regions, there seemed to be twodifferent networks that correlated with different aspects of thedisorder. Thus, each characteristic of the disorder may be treated byprimarily modulating the network correlated with the target symptom (andalso by countering any unwanted modulation of one system by anotherwhich occurs in response to neuromodulation intended primarily foreither system). In other words it is not enough to merely look forabnormal hyper-hypo activation, but rather treatment can target theregions of networks which are related to the symptoms for whichtreatment is sought. Further, not only activations, but alsoconnectivity was found to be altered, suggesting that modulation of theinteractions of neural areas engaged by the network may be just asimportant as normalization of activation, in the treatment of thedisorder.

Lastly, the affective catatonic symptoms were closely related todysfunction in the orbitofrontal cortex, while the alteration related tomedial prefrontal cortical network was more associated with emotionalprocessing. Again, the target regions of the brain network should bechosen, and neuromodulation provided, according to the treatment goals.Northff (2002) has also implicated this prior brain network usingLorazepam, an antidepressant, which led to the reversal inorbito-frontal activation patterns. Further Northoff (2000) demonstratednegative emotional processing can be characterized by strong and earlymedial orbitofrontal cortical activation, whereas positive emotionalprocessing showed rather later and weaker activation in lateralorbitofrontal/prefrontal cortex. This study is important because itargues for a functional dissociation between medial and lateralorbito-frontal/prefrontal cortex during negative and positive emotionalprocessing, lending additional support to the assumption of a functionalsubdivision of two separate brain networks within the orbitofrontalcortex. Further it shows a temporal dynamic of a network, where thetiming of the activations of different parts of the network, and themodulation of temporal order of these processes, could be utilized intreatment

In the case of schizophrenia, and other complex psychiatric disorders,across the population the disorder may engulf a cluster ofheterogeneously distributed symptoms, traits, states, and symptoms.Further, within a single patient, several different networks may beprimarily responsible for different characteristics of the disorder. Forexample, using fMRI studies have found that a brain circuit, involvingthe right amygdale and the MPFC had functional abnormalities duringprocessing of emotion, suggesting a viable brain network for whichtreatment of dysfunctional emotional behavior in schizophrenia may beapplied (Takahashi, 2004). Tackling a different aspect of this disorder,an fMRI study related to visually guided saccades and antisaccades,reported involvement by cortical and subcortical networks (Matsuda etal, 2004), supporting a model in which the fronto-parietal circuit isrelated to the planning of saccadic eye movements that involve attentionand control, while the fronto-striato-thalamo-cortical circuits connectto cortical region as a feedback network. Accordingly, sinceabnormalities in spatial attention and eye movement control observed inschizophrenia may therefore stem from dysfunctions in thefronto-parietal and fronto-striato-thalamo-cortical circuits, thesebrain networks are appropriate targets for treating attentionalpathology in this disorder. Looking into yet a further aspect of thisdisorder, Schlosser et al (2003a,b), provided evidence for alteredconnectivity of brain networks underlying memory disorders inschizophrenia, for both treated and drug free schizophrenics using SEManalysis of fMRI data. The studies suggest that enhancedthalamo-cortical and cortico-cortical intrahemispheric connectivity maybe due to a compensatory increase of neuronal connection strength(consistent with a model of cortical inefficiency in schizophrenicpatients), or a deficient thalamo-cortical filter which does notsegregate/gate information normally. Further, lower interhemisphericconnectivity of the frontal and parietal association cortex was foundand was suggested as the functional correlate of reduced cognitiveperformance in schizophrenic patients. Therefore, the data from thesestudies provides two networks for which abnormal path coefficientsindicated abnormal coupling between structures as reflected bycovariance measures. These two networks could contain regions for thesensors/stimulators of a BND, and neuromodulation can be used to providetherapy which is geared towards deterring the network from producingthis diseased state characteristic. Additionally, stimulation couldoccur outside of the structures just described, for example in thethalamus, but treatment efficacy can be measured by normalization ofthese networks, from sensors located within the brain networks. Furtherevidence of relevant networks come from Hoptman (2004) who used DTI anda voxelwise correlation analysis, and associated compromised whitematter (measured by fractional anisotropy) with impulsivity inschizophrenia, in the left postcentral gyrus, right superior/middletemporal gyrus, and bilateral fusiform gyrus. These areas may thereforecomprise a fronto-temporo-limbic circuit that modulates impulsivity, atleast within this patient population. Clearly different brain networksunderlie the complex characteristics of psychiatric disorders andtherefore neuromodulation may attempt to differentially normalize, orotherwise modulate, each of these in order to treat a separate aspect ofthe disorder. Treatment should be guided not only by consideringactivation, but also relative activation, compensatory mechanisms, andthe normal/abnormal connectivity and interactions within the brainnetworks that underlie various characteristics of these disorders.

Recently, new techniques have emerged and are being applied to ascertainbrain networks which are responsible for a large array ofcharacteristics in normal, aging, and abnormal brains (Thompson et al,2004). For example, using modeling techniques, brain networks have alsobeen identified which may be relevant for the treatment of some paindisorders (e.g, one network includes cingulo-frontal cortex and themidbrain, Valet 2004), treatment of multiple sclerosis (Au Duong, 2005),and other disorders. Additionally, the right subdivision of the anteriorcingulate cortex (ACC) and the dorsolateral prefrontal cortex (DLPFC)have been shown to be components of a neural network which is abnormalin bipolar disorder, and which plays a critical role in the completionof tasks requiring self-monitoring and inhibition, functions often notedto be altered in bipolar patients (Staci et al, 2004). Theidentification of these brain networks 102 permits stimulation to beprovided to, and sensed data to be obtained from, relevant brain regionsduring the treatment of various brain disorders. Further, by providingstatistical summaries of the normal and abnormal values for differentmeasures in regions of the network, to which the relevant measures of apatient's brain network can be compared (e.g., using a Z-transform), thesuccess of a stimulation protocol can be assessed 108, and subsequentlyadjusted based upon this comparison. For example, the stimulationparameters can be changed 110 if various treatment criteria are not met.Using data collected from the patient, information about the brainnetworks can be created using modeling methods (structural equationmodeling or “SEM”, dynamic causal models or “DCM”, brain electricalsource analysis “BESA”), and correlation techniques (e.g., partial leastsquares “PLS”), where, for example, a relevant brain network can beidentified 102 as the regions (reflected as imaged voxels of a neuralregion) which show covariance with a characteristic of the disorder(i.e. seed PLS). Accordingly, a brain network may be identified as acircuit which is established by imaging methods as correlated with atleast one characteristic of a mood, anxiety, or other psychiatric orneurological disorder. The imaging methods can detect this correlationusing an analysis such as path analysis or other correlation-basedtechnique. Brain networks can be identified as a set of putativelyinteracting structures which seem to underlie (e.g., be correlated with)a disease state or trait. Brain networks can also be identified while apatient is provided with one or more medications in the treatment of adisorder, and can be identified used neuroimaging data obtained before,during, and/or after exposure to medication, or across different dosesof a medication,. Networks can also be identified during performance ofa task, during rest, or during exposure to emotional or neutral stimuli.In summary, neuroimaging data collected over a wide variety of tasks andconditions may be used to identify regions of the networks 102 whichwill be modulated during treatment, locate appropriate regions, forexample, to guide surgical implantation of sensors and stimulators 104,to define treatment criteria, to evaluate neuromodulation duringtreatment 108, and to adjust the neurostimulation protocol 110 when theevaluation of neuromodulation treatment indicates a change is necessary,for example, in order to meet treatment criteria.

Alterations in brain networks are not present merely in brain disorders,but also occur as a part of normal aging process. Analysis of fMRI data,for example, by PLS/SEM (Grady et al, 2003a,b; Grady et al, 2005) hassuggested that both normal elderly and Alzheimers patients establishdifferent networks than normal young controls during memory tasks,implicating compensational brain networks which may assist thehippocampus to adaptively compensate for age related decrements inneural resources. Interestingly, the metabolism or “functionalactivation” was normal in the hippocampus of the elderly, and it wasonly by examining the functional connectivity of the brain networkswithin which this structure was activated, that compensatory activitywas detected. This provides further support that the relative activationof a region should be understood in the neural context of the activatedbrain network and functional connectivity of the network, as may bereflected as path coefficients in some neural modeling. A network maycontain all the structures implicated in a disorder, or may contain onlya subsection of the network responsible for a particular characteristic

In one embodiment of a treatment protocol which addresses compensatingfor abnormal connectivity, the activity of one region of a network isused to guide the neurostimulation of at least a second region of thenetwork. Rather than just increasing the activity of a second region ofa network, the aim is to correlate the activation of this second regionso that its activity is more (or less) correlated with activity in thefirst region, since neuroimaging data (such as network modeling, innormals, or population norms for imaging data e.g., QEEG normativeprofiles), indicates that the two regions are normally more coherent.For example, as illustrated in FIG. 2G a sensor can be placed in thefirst region of the network, and the sensed activity of this firstregion is obtained 172 and used to create the neurostimulation signal,or/and adjust the stimulation protocol 1 174, which is applied to thesecond region 176, thereby modulating the relationship between the tworegions, for example, increasing their coherence. Adjusting thestimulation protocol 1 174, may include introducing a lag term into thestimulation protocol for the second brain region, so that it isstimulated with a lag. The lag may be based upon a self or populationnorm, and introduces a delay rather than having the intended activityoccur in the two areas at substantially the same time. By changing thefiring patterns, activation levels, or other characteristics of thesecond brain region of the network, that region can become more or lessreceptive to the input of the first region, and the stimulation will actto drive or entrain the activity of this second region so that afferentinput from the first region is enhanced. Further, in some cases, if boththe first and second regions of the network communicate with a thirdregion, then by linking the stimulation of these two regions, theirinfluence on a third region can be altered, e.g., become normalized.Accordingly, correlation analysis of data from brain networks can beused guide neurostimulation protocols, where the aim is not to increaseor decrease the overall level of activity, but rather to alter thetiming and correlation, of activity between the two regions of the brainnetwork.

Pre-treatment imaging data may be used to determine sites of a networkand stimulation parameters. The treatment may be one or more ofpsychological therapy such as cognitive-behavioral therapy, an ingesteddrug, neuromodulation by an implanted device. Post-treatment imagingdata may be used to determine stimulation parameters, where thestimulation occurs at all sites or a subset of sites, while a patient ismedicated or non-medicated, where stimulation has been recently turnedoff, or has been off for an extended period of time to permit symptomsto return.

In a set of specific examples of this method, imaging data can bestatistically compared to prior datasets related to different types ofprior populations. John et al (1994) has shown that topographic QEEGmaps can be used to subtype disorders such as schizophrenia, intoprofiles that share common features. These feature clusters can be usedto select appropriate pharmacological therapies based upon thesuccessful therapies of prior patients who demonstrated similarprofiles. Accordingly, in one method, imaging data of the individual iscompared, for example, statistically compared, to a database, containingimaging data of individuals with different disorders and who haveresponded to different neurostimulation treatments, in order to classifythe subject and provide the appropriate therapy. In one embodiment theimaging data is analyzed by software that provides a model of brainnetworks. These brain networks of the individual can be compared to adatabase of brain networks, in order to classify the brain networks ofthe individual into an appropriate subtype. Both implantation andsubsequent treatment protocols can be based upon the classification ofthe features of the individual's brain networks with respect to thesubtypes of the database.

Lastly, it should be noted that commonly known psychiatric (and otherbrain) disorders are largely thought to be heterogeneous, withindividuals classified as having a particular disorder often manifestingunique clusters of symptoms. Further, the neural basis underlying aparticular symptom may be different in different individuals. Althoughthere is some evidence for final common pathway, or in other words, acommon neural pathology which is shared by patients who manifest similarsymptoms, clearly heterogeneous response to pharmaceutical treatmentreflects that the overlap across individuals is not complete.Accordingly, when designing a treatment protocol (i.e., the targetsintended for neuromodulation, the modality of neuromodulation, the drugsto be used, and the neuromodulation parameters) which is to beimplemented, relying upon information about the brain network, ratherthan, or in addition to the behavioral symptoms, may provide for moreaccurate treatment. By evaluating the brain network of the individual, adirect measure of the pathology can be used to create an appropriatetreatment protocol, For example, in one method, measures from a brainnetwork of an individual can be statistically compared to differentclusters in a database, in order to classify the network of anindividual into a particular subclass. One type of classification can berelated to treatment successes, wherein different subclasses of networkswhich have been shown to normalize when stimulation follows aparticrrlar treatment protocol created. Classification of the patient,guides the selection of the treatment protocol for that individual.Accordingly, evaluating neural network data can be used to select thenumber, location, and type of neuromodulation that may be successful innormalizing the network, and consequently increasing the chance forproviding successful therapy for the behavioral and cognitive symptomsof a disorder. In one method the steps for treating a brain disordercomprise; sensing neuroimaging data, evaluating neuroimaging data toprovide at least one measurement of a brain network, performing acomparison of this measurement of a brain network to a database of twoor more classes of brain networks and, using the results of thiscomparison to assist in selecting a treatment protocol including animplantation protocol.

Neuromodulation of Brain Networks in Treatment.

During the post-surgical treatment of a patient, the parameters of theneurostimulation protocol can be iteratively determined by performing anassessment process, which examines changes which occur in the brainnetworks associated with the disorder. During the assessment process thecreation of the neurostimulation protocol can be made based upon senseddata obtained from implanted sensors that measure the network's activitywith respect to various aspects of electrical activation, biochemical ordrug levels, neuronal firing, metabolism, and other measures for whichsensors have been implanted. Alternatively, this determination can beused based upon sensed data which is neuroimaging data obtained fromexternal sensors. Activation of different regions of the network, aswell as other characteristics of the network can be obtained by modelingthe imaging data and can be used to guide the neuromodulation protocol.The neuroimaging data can be sensed data that is collected duringneuromodulation using a treatment protocol which stimulates the targetregions, or only a portion of the neural targets, within at least onenetwork which putatively underlies a characteristic of the disorder.This data can be used to determine the effects which stimulatingportions of the network have on other portions. The treatment protocolcan incorporate information about the inter-region interactions, forexample, in the form of linking rules which change stimulation of 1target region based upon the stimulation at least one other targetregion. Alternatively, treatment may be halted several seconds, minutes,hours, or days prior to the assessment procedure. Alternatively, senseddata obtained during both a “stimulation-on”, and “stimulation-off”assessment period may be combined in the assessment procedure.

In another embodiment, the sensed data can be used to modify stimulationprotocols, whereby the sensed data is processed to provide result data,and result data can be evaluated to adjust the neuromodulation protocol.For example, electrophysiological data is sensed from electrodes locatedin or near a structure of brain network. The sensed data is processed,for example, amplified and filtered, and the power within a specifiedband is measured to yield result data. The result data is evaluated, forexample, compared to a treatment criterion, which may be based uponreference data. The success or failure of the result data to meet thetreatment criterion will determine if stimulation parameters aremaintained or adjusted, respectively. In another example, the resultdata are processed by mathematical models which evaluate the brainnetwork, such as path models. This modeling produces result data whichcan be compared to treatment criteria in order to determine if treatmentshould be initiated, or, if already occurring, determine if it shouldcontinue with or without adjustment. The result data can be stored in adatabase (where it can then serve as reference self-norm data) locatedeither in the implanted BND of the BMS or can be transmitted to adatabase which resides in external computer equipment such as anexternal patient programmer. The modeling algorithms can use informationabout endogenous electrical or chemical activity, or both. For example,MRS allows quantification of neurotransmitter levels in differentregions of the network. Models of brain networks can be based uponneurotransmitter levels in several regions of a network, and therelative levels of these regions. Concentrations of a substance relativeto the same or different substance in other brain regions (e.g., 5HTlevels in region 1 vs GABA levels in region 2) can be used to guide theelectrical, chemical or other type of neuromodulation of a target brainregion.

Treatment may consist of preventing, deterring, ameliorating, orcompensating for abnormal brain activity of a brain network which isputatively related to one or more aspects of the condition for whichtreatment is sought. Treatment can be provided for one or more braindisorders, for one or more brain networks, and the symptomatology can becan be a mixture of one or more pathologies. For example, clinicaldepression is a syndrome composed of a cluster of symptoms which mayinclude negative mood, anxiety and somatic symptoms, apathy, vegetativeand hormonal changes, motor slowing, and cognitive impairment. Treatmentcan be directed towards improving any one or more of these symptoms.Further, across different disorders, the symptoms for which treatment issought can be either behavioral, cognitive, abnormal neuroimagingresults, or a combination of these. Additionally, treatment can beoriented towards modulating brain networks related to both traits andstates associated with a disorder, or which have been related totreatment refractoriness in a disorder.

Various methods of treating a brain disorders may comprise additionalembodiments. For example, sensed data obtained from a sensed neural areamay be used to modulate at least two target neural areas of a relevantbrain network thereby treating the brain disorder. Alternatively, aleast two sensors placed in two sensed neural areas of a relevant brainnetwork may be used to adjust modulation parameters for at least onetarget neural area of a relevant brain network thereby treating thebrain disorder. Further, neuromodulation for treating a brain disordermay simply consist of modulating at least two target neural areas of arelevant brain network. In another embodiment, neuromodulation of one ormore target areas, using two or more neurostimulation protocols, resultsin the differential modulation of neuronal activity in one or more otherbrain areas of the identified brain network (e.g., see FIG. 2C and FIG.2D). The modulation of at least one target area of a network can providetreatment by causing an increase, decrease, normalization, or other typeof modulation in at least two other brain areas of the identified brainnetwork. A brain network can be two or more brain regions whichcommunicate with each other, and modulating the activity in a firstregion alters, at least a portion of the electrical or chemicalcharacteristics of the second region.

The brain disorder which is to be treated may be a mood and/or anxietydisorder and at least one brain region for sensing or stimulating is abrain area in a network which includes a subcallosal area. The mooddisorder may be selected from, for example, the group consisting ofmajor depressive disorder, bipolar disorder, dysthymic disorder, or ananxiety disorder such as a panic disorder, posttraumatic stressdisorder, obsessive-compulsive disorder or phobic disorder. The“subcallosal area” generally includes medial gray and white matter underthe corpus callosum, as well as white matter tracts that are associatedwith the subcallosal area, afferent and efferent projections from thesubgenual cingulate area, subcallosal gyrus area, ventral/medialprefrontal cortex area, Brodmann areas 10, 24 and 25, and closelyadjacent neural tissue that regulates or is regulated by thesestructures. Accordingly, treatment should result in the desiredmodulation of activity in at least one brain area of an identifiednetwork which includes the subcallosal area as one of its structures. Inone embodiment, the brain disorder is a mood or anxiety disorder and atleast one target neural area and/or sensed neural is/are chosen from atleast Brodmann 25, Lateral prefrontal cortex (LatF9), anterior thalamus,anterior cingulated, subgenual cingulate, orbital frontal cortex,hippocampus, and medial frontal cortex. Further, in order to modulatethe symptoms of depression and anxiety, which often coexist within thedepressive disorder, cortico-limbic patheways can be modulated whereinmodulation selectively modulates dorsal cortical activity to modulatesadness, and ventral cortical activity to modulate anxiety (Liotti &Tucker, 1995).

As mentioned earlier, a brain network can be comprised of severaldivisions (i.e., nuclei), within a particular brain structure. Forinstance, the cingulate generally acts as a relay nucleus whichmodulates activity between the cortex and limbic areas. Within thecingulate are many specialized subdivisions with unique properties anddifferent roles, which are determined in part by the pathways whichterminate within each area. For example, within the cingulate, Cg25 is aventral division which is flanked by Cig24 a-c as one moves away in ananterior-dorsal direction. Also, closely adjacent is the posteriorcingulate (Cg30,Cg31). It is important to consider that divisions withina structure can modulate activity in other divisions of that structure,either directly, or via multi-synaptic pathways. The close proximity ofdifferent subdivisions within a structure increases the risk that themodulation (e.g., electrical field) of one structure can directlyinfluence a different structure and result in unwanted side-effects. Inother words modulation of one network can unintentionally cause themodulation of a different network since structure for the two networksreside in close physical proximity. One solution to this problem is amethod of modulating a brain network, as illustrated in FIG. 2H whichincludes implanting at least a first stimulator and a second stimulator178, adjusting a first modulation protocol and modulating a first brainarea to relieve one or more symptoms of a brain disorder 180, andadjusting a second stimulation protocol and modulating a second brainarea to relieve side effects produced by the modulation of a first brainarea 182. In one example, the a first stimulator, for simulating a firstbrain region is implanted in sufficiently close proximity to a secondstimulator, which stimulates a second brain region, that the firststimulator directly modulates the brain area which is modulated by thesecond stimulator. The stimulation protocol of the second stimulator isadjusted to stimulate this second brain region so that this stimulationdecreases unwanted side-effects produced by the neurostimulationprovided by the first stimulator. The first and second stimulator can betwo or more electrode contacts on a single electrical lead, each ofwhich modulate the same brain network. Alternatively the method includesimplanting two or more electrical contacts in adjacent brain regions,and providing a stimulation signal to the first contact to primarilymodulate a first brain region in order to treat a symptom of thedisorder, and providing a second stimulation signal to the secondcontact, to primarily modulate a second brain region, and adjusting thesecond stimulation signal to decrease the side-effects produced by theeffects of the first stimulation signal.

Treatment of the network can be directed towards, and guided by, changesin the psychological or behavioral state of a subject, such as enhancingthe subject's mood, or changes in the results of analysis of imagingdata, including analysis of active regions, correlation analysis,partial-least squares analysis, and path analysis such as SEM. Theanalysis of a patient's brain activity can be used to guide at least onecharacteristic of treatment including the determination of at least onesensor location, target location, at least one characteristic of thestimulation protocol, at least one characteristic of the sensingprotocol, and analysis protocol. The analysis protocol can utilizesensed data obtained from two or more regions of a network. Duringtreatment, the sensed data from two or more regions of a network can becombined, compared, or otherwise incorporated into the analysisprotocol, in order to determine if, for example, these regions are beingrelatively modulated in a desired manner or if adjustments need to bemade to the stimulation protocol.

In addition to electrical stimulation, the BMS can utilize an infusionsystem configured to dispense one or more drugs in order to providetherapy to an abnormal brain network. The drug can be, for example, oneor more of the following: a neurotransmitter agonist, a neurotransmitterantagonist, an inhibitory neurotransmitter upregulation agent.Pharmacological neuromodulation of two or more areas can be guided bylinked rules in order to cause the relative activity to reach desiredlevels in these areas. Obviously, the BMS can be configured to dispensea drug to one target of a network and also to electrically stimulate asecond target of the network.

In another embodiment, the system for stimulation of a network comprisesat least one device having at least one sensor and at least onestimulator which can sense/stimulate at least one brain area of apathological network. As shown in FIG. 4, the sensor can be part of asensing subsystem 32 and the stimulator can be part of a stimulatorsubsystem 30, both of which may be coupled to a controller subsystem 34in order to link the stimulating to sensing, and thereby provideresponsive neuromodulation of a network to treat a characteristic of abrain disorder. The sensors and stimulators can be either functionallycoupled to a BMS, or incorporated within it. If the neuromodulation iselectrical the stimulator should include at least one electricalcontact, and if chemical, then it should comprise at least one catheter.The stimulator can also contain a sensor for sensing data from one ormore brain regions. The processor in the control subsystem may evaluatethe sensed data and deliver neuromodulation according to a treatmentprotocol. If the brain disorder is a mood and/or anxiety disorder thenat least one sensor and/or stimulator is located to permit stimulationor sensing of a brain region of the network, which includes asubcallosal area.

A “normal network state”, occurs when the characteristics of a brainnetwork, comprised of at least two brain regions, associated with anunwanted characteristic of a brain disorder, pass the one or moretreatment criteria set for the network. An “abnormal network state”occurs when the characteristics of a brain network, of at least twobrain regions, which are associated with an unwanted characteristic of abrain disorder, fail one or more treatment criteria set for the network.Neuromodulation treatment is designed to convert an abnormal networkstate into a normal network state, or to prevent, deter, or decrease theprobability, frequency of occurrence, and severity of at least oneabnormal network state. An individual may express a number of differenttypes of normal and abnormal network states, due in part, to theexistence of different endogenous states, for example, while awake andasleep (while the network may be vastly different between both thesestates, these may both be normal). The evaluation of sensed data can beused to determine when the network enters into a different state, forexample, discriminant analysis can be used to classify the current stateinto one of several predefined states as defined, for example, by themedical personnel or normative data. “Discriminant analysis” per se,does not have to be the full analysis, but rather only the generation ofa score used to classify the current state. Alternatively, a simplemultivariate equation, template matching algorithm, patient input usingthe external patient programmer or other means can be used to quicklyand accurately classify the state of the network without requiring thesame amount of computational resources, Accordingly, differentneuromodulation protocols and treatment criteria may be invoked during anumber of different normal and abnormal states. This strategy ispromoted by the evidence that neural activity of a region must beunderstood in the larger neural context of the network(s) of which it isa part, in other words the stimulation protocol and treatment criteriashould be adjusted based upon activity across the network. In oneembodiment of treating a brain network using neuromodulation, the stepsfor making the adjustment to the treatment protocol can comprise:sensing sensed data, processing sensed data to obtain result data,evaluating the result data to define a current network state; selectingtreatment criteria associated with the current network state; evaluatingtreatment by comparing sensed data to treatment criteria and taking someaction such as stimulating, or modifying the neurostimulation protocolif the treatment criteria fail to be met.

Neuromodulation treatment is not limited to increasing or decreasingactivity of a region, but can also simply alter firing patterns of theregion, for example, so that neurons increasingly fire in a burst or nonburst mode, fire at a particular frequency, or fire only in response toactivity at other areas of the brain network Treatment stimulation canaim to normalize an established brain network by sensing at least afirst brain region and a second brain region, and stimulating at least afirst brain region, according to data sensed in both of these areas,wherein said first brain region and second brain region have been shownto be part of a brain network underlying the a disorder for whichneurostimulation is intended to serve as treatment. Treatment can alsoattempt to normalize a brain network associated with a brain disorder bysensing at least a first brain region and a second brain region, andstimulating in at least a first brain region, wherein stimulation ofsaid first brain region is designed to a change in the activity of saidsecond brain region. The change is a modification at least onecharacteristic of said neural activity, for example, a change in thedominant frequency, amplitude, or other change in the brain activity, orneurotransmitter level, of said second brain region. The modulation canuse the data sensed in the first brain region to stimulate a secondbrain region, for example, in order to increase the coherence of the tworegions. Neuromodulation can occur both chronically and/or responsively,in relation to changes in the network, or can occur according to patientrequest.

An alternative method of treatment which can include uniquely treatingat least two symptoms of a patient with a psychiatric/mood disorder, andcan comprise: implanting a control subsystem in the patient whichcontrol a stimulation subsystem which provides the delivery of at leasttwo digital stimuli which are converted into stimulation signals tomodulate at least two areas of the brain which primarily affectdifferent symptoms of a disorder; and applying the at least twostimulation signals to at least two areas of the brain in order toalleviate, at least in-part, two or more symptoms of the disorder of thepatient being treated. These brain areas can be part of a brain network,underlying two or more characteristics of the disorder, or can be partof different networks which do not interact. Further in this method, thestimulation of target structures which, for example, normally exhibitdecreased activity which correlates with characteristics of thedisorder, which is a depressive disorder, may be excitatory. Further inthis method, the stimulation of target structures which, for example,normally exhibit increased activity which correlates withcharacteristics of the disorder, which is a depressive disorder, may beinhibitory. Additionally, in some embodiments, the at least twostimulation signals are applied to two or more targets of a networkincluding the hippocampus, insula, right middle temporal gyrus,occipital cortex, temporal cortex, hypothalamus, anterior pituitary,posterior pituitary, right posterior temporal lobe, anterior thalamus,motor cortex, and premotor cortex.

In an alternative method, treatment includes inhibitory neuromodulationof at least two areas of a brain network correlated with symptoms ofelevated mood and/or anxiety. Neuromodulation includes at least onestimulation signal which is transduced to provide stimulation todecrease excitement of the at least one area of this network whichnormally exhibits increased activity. In an alternative method,treatment includes excitatory neuromodulation of at least two areas of abrain network correlated with symptoms of elevated mood and/or anxiety.Neuromodulation includes providing at least one stimulation signal toprovide stimulation to increase excitement of the at least one area ofthis network which normally exhibits decreased activity. In analternative embodiment, stimulation to one region is excitatory, whilestimulation to a second region is inhibitory. The stimulation can beapplied, for example, to a network including one or more of thehippocampus, insula, right middle temporal gyrus, occipital cortex,temporal cortex, hypothalamus, anterior pituitary, posterior pituitary,and right posterior temporal lobe.

Neuromodulation of Brain Networks: Stimulation Linking Rules.

FIG. 3A shows a diagrammatic example of two brain regions A and B whichrepresent target areas which stimulated to treat a brain disorder. Inthis hypothetical example, stimulation treatment may occur at eitherbrain region, and the stimulation protocol does not compensate or adjustfor any interactions or connections between the regions, the assumptionbeing that these are not relevant. This model reflects assumptions ofthe strategies used in the prior art, where neurostimulation of oneregion, for example A, is carried out without consideration of theeffects of this stimulation upon other areas of a brain network, forexample B. FIGS. 3B to 3G show alternative diagrammatic examples inwhich two or more brain structures are involved in simple brainnetworks. The solid lines represent positive correlations, whereexcitatory stimulation in one brain structure increases activity atanother structure. The thickness of the line indicates the strength ofthe relationship. Dashed lines represent negative correlations, whereexcitatory stimulation in one brain structure decreases activity atanother structure. Actual brain networks can consist of many more brainareas, and significantly more interactions, including reciprocalinteractions, between these structures.

When stimulating brain networks the stimulation protocols of currentinvention can incorporate these interactions in order to more accuratelyand efficiently provide treatment, by differentially modulatingdifferent brain regions in an intended fashion. For example, linkingrules can be used during neurostimulation treatment to adjust for one ormore interactions between brain structures. Linking rules can alsoenable stimulation of the network to reinforce relative activity levelsbetween different brain regions, by changing stimulation in one area asa function of stimulation provided, or data sensed, in another area. Insome embodiments, linking rules may be adjusted over the course oftreatment, as the interactions between structures change due tocompensatory or other alterations in regions of the network. Theseadjustments can occur based upon sensed data which is evaluated in orderto quantify the effects which stimulating one area has on other areas,and if these have changed, the linking rules are modified accordingly.Linking rules can therefore be used to address the effects of indirector secondary stimulation. “Indirect stimulation” effects can occur atlocations which are sufficiently distal from the site of stimulationthat these areas are not directly stimulated by, for example, theelectrical field of a stimulator. Instead, indirect stimulation can bemediated by stimulation of a first region which sends efferents to asecondary region, where the secondary region is part of a brain networkof which the stimulated region is a part. Indirect stimulation reliesupon, and adjusts for, connectivity between brain structures of anetwork.

It should be noted that the use of linking rules does not necessitatedirect connectivity between the regions which are being stimulated. Forexample, in FIGS. 3C-3E a linking rule may modulate the stimulation oftarget A in accordance with stimulation of neural target B, in order tocontrol the modulation of area C. Even though stimulation targets A andB are not directly connected, or do not directly influence each other,they both contributed to the excitation of area C, and so stimulation ofeach area should take into account simultaneous stimulation in the otherarea. Linking rules can become critical even when brain stimulation isapplied to relatively separate regions in the brain. For example,linking rules can be applied in treatment which includes bilateralstimulation of contra-lateral structures, and may be used, for example,to synchronize or desynchronize two or more regions of the brain whichreside in separate hemispheres.

It should also be noted that regardless of the strategy guiding thecreation of the stimulation protocol, including the creation ofstimulation signal itself (e.g., if its characteristics are generated inresponse to sensed data), which is to be used to modulate two or moreregions of a network, this strategy can be altered according to linkingrules. When control laws are used to govern the stimulation of differentareas of a brain network, the selection and adjustment of these laws canbe restricted by linking rules. Further, regardless of the methods usedto process the sensed data and/or provide stimulation (e.g., use ofneural network analysis, genetic algorithms, bayesian networks, decisiontrees, calculation of a measure of chaos, calculation of entropy,calculation of a maximal state control, calculation of seizureprediction, calculation of tremor size, calculation of relativeactivation levels in different parts of the brain) the use of linkedrules can be incorporated. Linking rules can be used for both generatingthe stimulation signal and also for adjusting the neurostimulationtreatment. Linking rules can also be relied upon for the stimulation ofa single target area, if it is the case they these are used to adjustdifferent protocols that are designed to indirectly modulate two areasof a network. For example, linking rules can guide the stimulating onetarget region using more than one protocol in order to obtaindifferential modulations of secondary regions where the time spentstimulating with each protocol is dictated by a linking rule.

Generally, linking rules which are to be used during the neuromodulationmay be implemented based upon: data collected during assessmentprocedures; based upon normative data; or based upon the experience ofthe patient. In one embodiment, neuromodulation of a network occurs bymodulating at least a first neural target region (i.e., NT1) and asecond neural target region (NT2), which are part of a networkunderlying, or significantly correlated with, at least onecharacteristic of a disorder for which treatment is being sought. Oneexample, of “linked stimulation” is that when at least one stimulationparameter for stimulating NT1, for example, voltage level, is increasedby 1 volt then simultaneously the neuromodulation of NT2 is increased by0.5 volts. Whenever NT1 is additionally increased by 1 volt, then NT2 isincreased by 0.5 volts. The “linking rule” is that Vnt2=Vnt1*0.5, whereVnt1 is equal to the voltage used at target NT1, and Vnt2 is equal tothe voltage used at target NT2. This rule could be used in thehypothetical system shown in FIG. 3E, where target A is stimulated withVnt2, while target B is stimulated with Vnt1. In this case simultaneousstimulation of A and B results in no change in region C of the network.If A and C are both related to one the pathological characteristicrelated to the disorder, and A fails to meet a treatment criterionindicating that it is hypoactive, while C is almost hyperactive, then bynormalizing A, without also stimulating B, C would become hyperactive.If area A is related to depression, while C is related to anxiety, thenmaking C hyperactive could hypothetically cause the treatment of asymptom of depression to result in the emergence of, or an increase in,anxiety or mania. It is also possible that linked rules could have beenused to directly stimulate region C with inhibitory stimulation, butstimulating B could be better in some instances. For example, if B isrelated to a different aspect of the disorder which could be treated,then providing stimulation at C would not enable modulation of B. Inanother example, an increase of voltage by 1 volt at NT1 leads to adecrease at NT2 of 0.5 volts. The “linking rule”, in this case, isVnt2=Vnt1*0.5*−1.

Multiple linking rules may be combined. For instance, these may becombined across stimulation of multiple neural targets of a network/:the voltage at NT2 can be determined by two other neural targets. Acombined linking rule could be defined where an increase of 1 volt atNT1 leads to a decrease at NT2 of 0.5 volts, and an increase of 1 voltat NT3 leads to an increase in voltage at NT2 of 0.5 volts. In thiscase, the “linking rule” is Vnt2=(Vnt1*0.5*−1)+(Vnt3*0.5*), where ifVnt1=Vnt3, then no stimulation takes place at Vnt2 (or at least noadjustment in stimulation takes place at Vnt2 due to stimulation atthese other 2 area). In another example, multiple linked rules may berelied upon simultaneously, where (Vnt2*0.5)*I=Vnt3 and(Vnt1*0.5)*E=Vnt3, may be used when NT2 is an area that is abnormallyhyperactive, and which is upregulated by activity at NT3 (and inhibitorystimulation of NT2 compensates for secondary stimulation which is aside-effect of direct excitatory stimulation of NT3), and NT1 is an areathat is hypoactive, and which is downregulated by excitatory stimulationat NT3, and NT3 is occasionally hypoactive and must be stimulated withexcitatory neuromodulation. The designation “*I” and “*E” provideneurostimulation patterns that inhibit (suppress) or excite (increase)neural activity in the target region. Accordingly, without the linkedstimulation rules, stimulation of NT3 in attempt to normalize theactivity of that region, would cause the activity in NT1 and NT2 tobecome more abnormal, although other areas (e.g., NT4), may arbitrarilybe correctly modulated by such treatment stimulation.

Linking rules are important because changes within the network, thatoccur as side-effects in other regions due to stimulation of a targetstructure, may aid, hinder, be irrelevant to, or may compensate forneuromodulation treatment in the target region. It various cases, thesesecondary changes may or may not be beneficial and may even act tomodulate different symptoms of the disorder from the one that isintended for treatment. For example, Bench, Friston, Brown, Frackowiak,and Dolan (1993) used factor analysis on depressed patients' symptomratings and identified three factors: anxiety, which correlatedpositively with rCBF in posterior cingulate and bilateral inferiorparietal lobules; negative mood and psychomotor retardation, whichcorrelated negatively with rCBF in the left dorsolateral prefrontalcortex and left angular gyrus; and cognitive performance, whichcorrelated positively with rCBF in the left medial prefrontal cortex.Accordingly, if neuromodulation decreased anxiety by inhibiting activityin the posterior cingulate, and this led to changes in the left angulargyrus, then negative mood might be simultaneously increased as aside-effect. By also stimulating the left angular gyrus, both symptomscan be successfully treated in a selective manner. In another example,down-regulation of dopamine-based neural regions in the treatment ofpsychiatric disorders may co-occur with symptoms of movement disorders,since both A9 (extrapyramidal motor/nigrostriatal system) and A10(ventral tegmental area VTA) are regulated by dopamine, although onlythe latter region is relevant to the positive symptoms of the disorder.If stimulation of a neural target, or treatment with an antipsychoticdrug, caused decreased activation in both of these structures (e.g., seeFIG. 3G, where downregulation of C decreases activation of both A andB), then this change would not be desirable in A9, since it merely leadsto movement related abnormalities. Accordingly, inhibitory stimulationshould occur in A10 while excitatory stimulation occurs in A9, tocounter the down-regulating effects caused by electrical or chemicalmodulation elsewhere in the network which affects both these structures.Similarly, in another embodiment, the fibers from the VTA which extendto the mesocortical system and the mesolymbic system can bedifferentially modulated, since these have been correlated withdifferent symptoms of the disorder (i.e. positive and negative symptoms,respectively). Using linked rules in the stimulation protocol to providecompensatory neurostimulation along the relevant fiber tracts, or withinthe different nodes that receive input from the VTA efferent fibernetwork, can compensate for stimulation of the VTA to increasinglyrestrict the resulting changes to the intended structures, while changesin other structures are inhibited or dampened. Alternatively, using twodifferent stimulation protocols which selectively modulate differentefferent fiber tracts of the network, which emanate from the samestructure, is a method which could address this issue. Further, the timeallocated for stimulating with one strategy could be determined by thetime used for stimulating with the other strategy. Additionally,restricting the time allocated for different stimulation protocols canbe provided by incorporating linked rules into the stimulation protocolwhere the linked stimulation characteristic is the amount of time forwhich the different protocols are used to stimulate a single region,rather than relating to protocols used in two separate regions.

In another example, the linking rule is again temporal, where for agiven duration of stimulation in NT1, an associated duration ofstimulation occurs for NT2. If stimulation at Nt2 occurs for a durationof the time that stimulation occurs at Nt1, the rule might beTnt2=Tnt1*0.5, where the stimulation at NT2 lasts for 50% of the timethat stimulation occurs at NT1. In another example, the linking rule isfrequency related where the frequency of stimulation for NT1, determinesthe frequency of stimulation which occurs at NT2. If the frequency ofstimulation at Nt2 occurs slightly lower than the frequency ofstimulation at Nt1, the rule might be Fnt2=Fnt1*0.95, where thefrequency of stimulation at NT2 is 5% slower than the frequency ofstimulation which occurs at NT1. In another example, the linking rule islatency related where the start time of stimulation for NT1, determinesthe start time of stimulation which occurs at NT2. If the time ofstimulation at Nt2 occurs slightly later than the time at whichstimulation occurs at Nt1, then the rule might be Lnt2=Lnt1*100, wherestimulation at NT2 begins 100 msec after stimulation begins NT1. It isobvious that the linked rules can be applied to any characteristic ofthe stimulation protocol, including pulse width, pulse frequency, pulseshape, stimulation time, frequency, voltage, current, and any otherstimulation characteristic that determines the treatment stimulation.The linked rules can be determined, and adjusted, based upon thefeatures of a model of the brain network which underlies the disorder,or the relationship between this model and a model of this same brainnetwork in normal brains, where the intent is generally to cause anormalization of the impaired brain network of the patient (see John etal, 1994 Seminowicz, 2004; Mayberg 2005). In addition to abnormally lowor high activity in a patient, relative to normal controls, in neuralregions of the brain network, the interactions and relations betweenthese regions can be used to guide the neuromodulation parameters. Forexample, linking neuromodulation in two areas can be used to attempt toincrease the correlation (path coefficients), between two regions of abrain network, which is decreased (smaller path coefficient), reversed(path coefficient with an opposite sign), or missing (a path coefficientwhich is normally expected was not fit by the path model), in theimpaired individual.

It should be understood that linked rules for stimulation can be used incombination with sensing. For instance, in one embodiment,neuromodulation of a network occurs by modulating at least a firstneural target region (i.e., NT1) and a second neural target region(NT2), which are part of a network underlying, or significantlycorrelated with, at least one characteristic of a disorder for whichtreatment is being sought,. Additionally, sensed data is obtained from asensor which senses at least one neural sensed region (i.e., NS1), whichmay, or may not, be the same as one of the neural target (i.e., NT)regions. In this example, when the data sensed at NS1 indicates that theneuromodulation of the network is needed and at least one characteristicof the neuromodulation protocol of NT1, for example, voltage level,should be increased, then simultaneously the neuromodulation of NT2 isincreased to 75% that of NT1 (since in this hypothetical example thelinking rule was Vnt2=0.75*Vnt1.

Additionally, linked rules can be applied to sensed data of the brainnetwork. For example, a first sensed neural region (i.e., SN1) and asecond sensed neural region (SN2) may be used to determine thestimulation parameters of at least one target (NT1). If thecharacteristic sensed at NS1, affects the neural network three timesmore than a characteristic sensed at NS2, then the rule might beVnt2=k*(Vsn1*3+Vsn2*1), where stimulation at NT2 is determined as 3times the voltage sensed at Vsn1 and 1 times the voltage sensed at Vsn2times a constant which results in an output voltage that is related tothe size of the sensed voltages and the characteristics of themeasurement circuit. Accordingly, both stimulation and sensing linkingrules can be based upon imaging data, sensed data, self-norms, andpopulation norms, related to characteristics of the network to betreated. In this example, Vsn1 and Vsn2 could be the voltage in aparticular frequency band, and Vnt2 can be an output voltage of anarbitrary stimulation signal that may not be related to the frequencyband used to estimate Vsn1 and Vsn2. Alternatively, Vnt2 could be Fnt2,where it is the stimulation frequency rather than voltage that isadjusted based upon the linking rule. Vnt2 could also be a variable suchas Bnt2, which is a measure of perfusion or bloodflow in that targetarea, in other words, the linking rules can functionally relatedifferent characteristics of the sensed and stimulation signals, and canbe implemented cross-modal.

In one method, a model of the network is built by iterativelystimulating one or more areas of the network and measuring the effectson other areas of the network. For example, one step is to stimulate NT1using 1 or more voltage levels or other characteristics of thestimulation signal and the next step is to examine changes which occurin the rest of the network. The next step is to adjust theneuromodulation protocols of other areas by incorporating linked-rulesso that these other areas are stimulated using one set of protocols whenNT1 is simultaneously stimulated (to counter the secondary effects), andanother set of protocols when NT1 is not stimulated. By iterativelystimulating different areas of the network and recording the changes atother areas, a model, or table of values, of the network and itsresponse to different types of stimulation, can be created. Thisprocedure can he done according to a protocol in the BMS, which may beoperated in conjunction with instructions inputted using the externalpatient programmer and can occur in a primarily automatic and fixedmanner or can he adjusted, according to an algorithm or according to thedecisions of a medical technician. The result may comprise a set oftransfer functions, which represent the effects/relationships betweeneach pair of regions of the network, for the different types and levelsof stimulation that exist in the stimulation protocol. These transferfunctions can then be incorporated into a set of multivariate rules thatguide neuromodulation of the network, as different brain areas aresimultaneously stimulated. Using this method or other methods which maybe more efficient, linking rules can be created and utilized by beingincorporated into the neurostimulation methods and systems of thecurrent invention.

It is obvious that linked rules for the evaluation of sensed data, aswell as linked rules for the stimulation characteristics, can becombined to determine the resulting neuromodulation protocolcharacteristics. It should also be recognized that linked rules may beincorporated into algorithms. may be conditional (i.e. only occur when acriterion is met), may be selected based upon detection of differentnetwork events, and can also be non-linear, and discontinuous, onlybeing implemented across certain ranges. For example, a linked rule maybe Vnt2=k*(Vsn1*3+Vsn2*1)while Vnt>2 volts and Vnt2=k*(Vsn1*5+Vsn2*1)while Vnt<2 volts. Linking rules can regulate using two different typesof parameters. The voltage at NT1 can be determined by the voltage atNT2 and the frequency at NT2, for example, Vnt1=Vnt2 and if Fnt2>80 thenVnt1=Vnt2+((Fnt−80)*0.5), where the voltage at NT1 is equal to the sumof the voltage at NT2 and 0.5volts for every additional 1Hz step, as themodulation frequency goes above 80 Hz. In another example, the frequencyat NT1 can be set equal to the sum of a constant voltage and a term thatvaries as a function of the voltage at NT2. Linking rules can be used toset the initial stimulation parameters, and also relied upon duringtheir adjustment during treatment, as may be required when evaluation ofsensed data, or simply a treatment program defined in the stimulationprotocol, indicates that such adjustment is needed. Accordingly, linkingrules can be used during steps 106 and 110 of FIG. 2 a.

Additionally, linked rules can be utilized by and incorporated into theexternal patient programmer. When using a patient programmer, andmanually increasing the voltage in NT1, a linking rule can cause correctadjustments to occur in the stimulation parameters of other neuraltarget regions. Further, in the same ways that current externalprogrammers allow patients to adjust stimulation parameters, the linkingrules can be adjusted by patients, within limits set by a physician.

Linking rules for sensing, evaluation and stimulation are important foraccomplishing various features of the invention. For example, these canbe used to provide neuromodulation of one region of a brain networkbased upon the characteristics of another region of the brain network,or based upon the relative activity which is sensed for the two regions.Relative activity may be measured as the electrical energy across acertain frequency band, which is sensed in one brain region and assessedin relation to either electrical or chemical activity in at least oneother brain region of the brain network hi other words, electricalenergy in one brain region can be compared to chemical activity orchemical levels in another brain region. Further, neuromodulation of afirst brain region can also depend upon combining sensed data from thatbrain region and at least one other brain region which has been shown toform a neural circuit The linked rule can state that stimulation of areaA must be increased until a measure that is sensed in area A is twice aslame as the size of the measure sensed at area B, and can also statewhether excitatory stimulation in area A must be increased, orstimulation in B must be decreased (or both must occur in proportion asspecified in the linked rule), until this is true. In this ease, thecombined activity can be evaluated with respect to treatment criteria.Additionally, the use of linking rules and treatment criteria may beused in a number of manners to address, utilize, and compensate forinterconnectivity of brain regions engaged by a brain network that is tobe modulated in order to provide treatment.

Brain Network Strategies for Decreasing Adaptation Effects.

While there are known strategies for combating the emergence ofadaptation to the neurmodulation, these usually employ methods that relyupon changing the neurostimulation signal over time within a specificregion. Varying the stimulation signal aims to decrease the type ofhabituation that may occur using a chronic and non-varying signal. Aunique solution to the problem of adaptation is to modulate areas of thenetwork so that different parts of the network are stimulated atdifferent times. Further, while certain areas are stimulated, apreviously stimulated area may not he stimulated or may be stimulated ata decreased level. This strategy can utilize information about theconnectivity and dynamics of a network in the creation of thealternative neuromodulation protocols. For example, if excitatorystimulation of a target region NT1 leads to increased activation at NT2and decreased activation at NT3, and this differential modulation isdesired, then it may be efficient and efficacious to simply stimulateNT1 and provide indirect modulation of these other structures (as wellas being more efficient for a power supply). However, if the neuralactivity in NT1 demonstrates adaptation to the stimulation signal, asreflected by a decreased modulation of NT1, NT2 or NT3 over time (as canbe reflected by sensed data values indicating that stimulation relatedeffects, stored in the database memory 38, were drifting upward ordownward over time), it may be beneficial to halt or attenuatestimulation at NT1 and initiate or increase stimulation directly ateither NT2, or NT3, or both (or to provide indirect stimulation via adifferent structure which also modulates NT2 and NT3). Accordingly,either in response to sensed data which indicates adaptation hasoccurred, or simply according to a protocol which changes over time,stimulation can alternate the specific neural targets of the networkwhich are stimulated, so that the overall desired neuromodulation of thenetwork is approximately mainttained Using this s type of dynamic anddistributed strategy. for modulating regions of a brain network, offersadvantages over, and can also be combined with, the know methods oftreatment. In one embodiment, the neurostimulation protocol can serve todecrease the effects of adaptation by alternating stimulation accordingto evaluation of sensed data so that the linking rules for stimulationare maintained (e.g. adjust stimulation at two stimulators until sensedactivity related to a relative measure is maintained within a desiredrange. The linked rules and the protocols can be contained within adatabase of the BND, and can be adjusted by the medical personnel orpatient using the external patient programmer. Using information aboutthe brain network can assist in circumventing adaptation effects bypermitting stimulation of different regions to result in approximatelysimilar types of modulation of the network. In the brain networkrepresented by FIG. 3 c, if sensed data indicates that modulation ofneural target. A begins to cause less of a change in C, then excitatorymodulation of neural target B can be initiated, rather than increasingthe amplitude of neurostimulation of neural target A. Further, in thebrain network, represented in FIG. 3 e, if sensed data indicates thatmodulation of neural target A begins to cause less of a change in C,then inhibitory modulation of neural target B can be initiated, ratherthan increasing the amplitude of excitatory neurostimulation of neuraltarget A.

External Patient Programmer

The external patient programmer can enable the patient to communicatewith the implanted neuromodulation device in manners which have beenextensively described by known art. For example the external patientprogrammer can allow patients to rate one or more symptoms orcharacteristics of their disorder, and also to modify neuromodulationparameters related to each aspect of the disorder. Unique from prior arthowever, are several features such as automatically adjustingstimulation to a second area if the stimulation in a first area isadjusted by the patient, as can be dicated by linking rules implementedby the device working jointly with the external programmer. This type oflinked rule implementation may be invisible to the patient, for exampleneuromodulation protocol related to the treatment of sadness may be bestprovided by adjustments for neurostimulation to areas NT1 and NT2, whereif the patient chooses to increase modulation directed at these areas,this increase occurs proportionately for the two areas, as defined bythe linking rule. Since it is a feature of the current invention todifferentially modulate unique regions of the network, if modulation ofa characteristic of the disorder relating to “indifference” may requiremodification of neuromodulation at NT3, NT2 and NT4, then in oneembodiment, this can occur with compensatory modulation of activity NT1and NT2, for any indirect changes which are consequentially produced.Accordingly, at least partially differential treatment of symptomsoccurs by allowing patients to modify parameters primarily related to aparticular symptom of their disorder. This may entail adjustingstimulation parameters only for a specific region of the network. Forexample, adjusting the treatment for “anxiety” may primarily causemodification of the protocol for neuromodulation of the posteriorcingulate and bilateral inferior parietal lobules; adjusting thetreatment of “negative mood” or “psychomotor retardation” wouldprimarily cause modification of the protocol for the left dorsolateralprefrontal cortex and left angular gyrus, increasing the treatment of“cognitive performance” would primarily alter the protocol forstimulating the left medial prefrontal cortex. Furthermore, the patientprogrammer may allow patients to specifically modify the protocolsrelated to hypothetical brain network 1, 2 or 3, each of which isprimarily related to one or more aspects of their disorder. The patientprogrammer can also allow patients to modify linking rules, withintolerance levels which may be set by a physician.

TMS and Alternative Embodiments

It is well known that TMS(e,g., repetitive TMS or “rTMS”) can be used tostimulate one or more brain regions, and therefore can be used todetermine the utility of stimulating different networks in particularmanners. This can be accomplished during an assessment procedure inorder to evaluate different brain regions which may be candidates forimplanted stimulators and sensors. Further, while the methods and systemdescribed herein have described using both implanted and externalcomponents, the invention can include TMS treatment for theneuromodulation of brain networks and can be completely external,although it may cooperate with implanted components. The methodsdescribed above are consistent with TMS treatment except that instead ofimplanting a device and providing an implanted stimulator which directlymodulates neural tissue, the modulation is provided by the TMS equipmentand protocol. In a general embodiment of the invention, TMS can used tomodulate at least two neural targets which are part of a brain network,according to the methods described herein, In an alternative embodiment,TMS is used prior to implantation to test and detect regions andparameters which would then be provided by the implanted devices usedduring treatment.

The BMS may be comprised of at least one device which is implanted inthe subject's body. Alternatively, the BMS can rely upon one or moreneurostimulators embodied within a single housing, or may be realized ina distributed design using spatially separate components which can beeither implanted or external or a combination of these two. For example,two or more Bion™ stimulators, which may be controlled by a singlecomputer system (or by a control subsystem of one of the Bion™stimulators), can be implanted in the brain of a subject to stimulate atleast two areas of the brain network.

Summary.

This specification has described a number of embodiments of methods andsystems for modulating brain networks in the treatment of braindisorders. A central feature is that the methods of treating acharacteristic of a brain disorder use a brain modulation system tomodulate at least two regions of a brain network and the stimulationprotocol for stimulating a first region is modified due to thestimulation protocol for stimulating at least a second region. Further,the stimulation protocol of a first region can be modified due to thesensed data of at least a second region. Both of these contingencies canoccur using a stimulation protocol that is defined or adjusted basedupon linking rules. When the BMS uses sensed data to provideneurostimulation, the evaluation of sensed data can cause stimulation tooccur responsively if sensed data indicates that a difference betweensensed data and a target reference value, as can be reflected in a BSV,fails to meet a treatment criterion.

Further, the linking rules can incorporate values derived from a modelof brain activity, an equation, an evaluation. of sensed data, andvalues obtained from a database. This feature therefore basicallyentails a method of implanting a brain modulation system and modulatingat least a first region and a second region of a brain network, whereinthe stimulation protocol of a first region is modified due to datasensed in, or stimulation that is provided at, at least a second regionof the network. When the BMS contains a sensing subsystem, a stimulationsubsystem, and a control subsystem, the control subsystem can containthe linking rules for guiding neuromodulation treatment in response tosensed data.

In another embodiment, a method of treating at least one characteristicof a brain disorder comprises performing stimulation to increase thenormalization of an established brain network. This can include thesteps of sensing a first brain region and a second brain region, andstimulating at least the first brain region. The first brain region andsecond brain region comprise at least a portion of a brain networkassociated with a disorder for which neurostimulation is intended astreatment, and normalization is related to at least one of electricaland chemical activity.

In the methods described herein the brain disorder can be a mood and/oranxiety disorder and at least one sensed area is a brain area in anetwork which includes a subcallosal area. Alternatively at least onetarget area is a brain area in a network which includes a subcallosalarea, but is not the subcallosal area itself. Further, the deviceprovides at least electric, magnetic, chemical, optical orpharmaceutical treatment to achieve modulation of the brain activity.The mood disorder can be selected as a major depressive disorder,bipolar disorder, dysthymic disorder, or an anxiety disorder which is atleast a panic disorder, posttraumatic stress disorder,obsessive-compulsive disorder or phobic disorder. Treatment also can beprovided for a psychiatric disorder which is at least one of psychosis,schizophrenia, and obsessive compulsive disorder. The method of neuronalmodulation of at least two target areas is intended to enhance thesubject's mood.

The method of treating a brain dysfunction which is a mood and/oranxiety disorder, may treat disorders including panic disorder,posttraumatic stress disorder, obsessive-compulsive disorder and phobicdisorder, and can include implanting at least one of the two stimulatorsin a target area which is a subgenual cingulate area. Further, thetarget neural area and/or the sensed neural area can he chosen from atleast one of: Brodmann 25, Lateral prefrontal cortex (LatF9), anteriorthalamus, anterior cingulated, subgenual cingulate, orbital frontalcortex, hippocampus, and medial frontal cortex, and the brain disorderis a mood or anxiety disorder.

The described systems can be used for treating patients withobsessive-compulsive disorder and neuromodulation is of a brain networkwhich includes the anterior limbs of the internal capsul.Neuromodulation can also occur for at least 2 regions, each of which hasbeen at least partially associated with a characteristic of a braindisorder. Alternatively, neuromodulation treatment is of at least 2regions, each of which has been primarily associated with acharacteristic of a disorder. The characteristics of this disorder canbe, for example, sadness, hopelessness, anxiety, antipathy, frustration,helplessness, lethargy.

Although the text of this specification often discusses treatment of atleast one network, it should be understood that neuromodulation systemscan be implanted bilaterally, and for a network in each hemisphere mayhe modulated based. upon sensed data or characteristics of theipsilateral network. Alternatively, neuromodulation of a brain networkscan be based upon sensed data, from the contralateral network, or may bebased upon data sensed from structures in networks on both sides of thebrain. Additionally, neuromodulation of a brain networks in onehemisphere can treat one characteristic of the disorder, whileneuromodulation of brain networks in the other hemisphere can treat adifferent characteristic of the disorder.

All patents, provisional and pending applications, and publicationscited herein, are incorporated by reference herein, as if included intheir entirety. In the claims of this application, when methods havesteps which have been assigned letters, the steps may occur sequentiallyin the order indicated by the letters, or certain steps may occurapproximately simultaneously, or in an interleaved fashion, with othersteps. The headers for various sections such as “Background” or“Treatment” are intended to be descriptive only, and do not limit thescope of the material which is provided in these sections.

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1. A method of treating at least one symptom of a brain disorder with aneurostimulation device comprising a first stimulator and a secondstimulator, the method comprising: operating the neurostimulation deviceto provide brain modulation of at least two regions of a brain networkaccording to a treatment protocol; wherein the modulation includes:modulating a first brain region of the brain network using said firststimulator according to the treatment protocol configured with a firstset of modulation parameters in order to provide treatment of thesymptom; modulating a second region of the brain network using saidsecond stimulator according to the treatment protocol configured with asecond set of modulation parameters in order to provide modulation todecrease a side-effect resulting at least in part from modulation in thefirst region; and, wherein, said brain network has least one brainregion associated with the symptom for which treatment is sought.
 2. Themethod of claim 1, wherein said treatment protocol uses linking rulesfor adjusting at least one modulation parameter, wherein the at leastone modulation parameter is selected from at least one parameter of: thefirst set of modulation parameters of the first stimulator formodulating a first brain region; and, at least one parameter of thesecond set of modulation parameters of the second stimulator formodulating a second brain region.
 3. The method of claim 2, wherein saidlinking rules are derived based upon at least one of: imaging data;sensed data obtained from at least one implanted sensor; a behavioralassessment of the patient; and subject report of the patient; and anetwork model.
 4. The method of claim 1, wherein brain modulation atleast one of the at least two regions of the brain network occurs atleast one of: periodically; continuously; in response to a patientrequest inputted using a patient programmer; according to a schedule orstrategy defined in the treatment protocol; and in response to the timeof day.
 5. The method of claim 1, wherein the side effect of modulatingthe first brain region relates to mood.
 6. The method of claim 1,further including sensing data from at least one area of the brainnetwork to obtain sensed data.
 7. The method of claim 6, wherein brainmodulation of at least one of the at least two regions of the brainnetwork is adjusted as a function of at least one of: the failure ofsensed data to meet a treatment criterion; the detection of an eventwithin the sensed data; the detection of a network event within thesensed data, and, a characteristic of a network event.
 8. The method ofclaim 6 in which said treatment protocol is adjusted based upon anevaluation of sensed data, said data comprising at least one of: therelative electrical activity in two or more regions of a network; and,the relative chemical levels in two or more regions of a network.
 9. Themethod of claim 8 wherein said chemical levels in the two or moreregions may be measured for at least one of: the same chemical; and,different chemicals.
 10. The method of claim 1 wherein said treatmentprotocol is adjusted based upon a comparison, said comparison being atleast one of the following: a. a comparison of the electrical activityin the first brain region of the brain network to the electricalactivity in the second brain region of the brain network; b. acomparison of the chemical activity in the first brain region of thebrain network to the chemical activity in the second brain region of abrain network; c. a comparison which includes both a and b; and, d. acomparison of the electrical activity in the first brain region of thebrain network to the chemical activity in the second brain region of thebrain network.
 11. The method of claim 1, further including sensing datafrom at least one area of the brain network, and adjusting the treatmentprotocol, based upon an evaluation of sensed data, said evaluationresulting in one of: a normal network state; and, an abnormal networkstate.
 12. The method of claim 1 wherein said treatment protocol ismodified with parameter values intended to do at least one of thefollowing: increase neural activity; decrease neural activity; alterfiring patterns of neural activity; promote firing in a burst mode;promote firing in a non-burst mode; promote firing at a particularfrequency; and promote activation in response to activity sensed at oneor more areas of the brain network, said one or more areas of the brainnetwork being either proximate or distal to the site of stimulation. 13.The method of claim 6 wherein the brain disorder is a mood and/oranxiety disorder and wherein at least one sensed area is a brain area ina network which includes a subcallosal area.
 14. The method of claim 1wherein the brain disorder is a mood and/or anxiety disorder and whereinat least one target area is a brain area in a network which includes asubcallosal area.
 15. The method of claim 1 wherein the treatmentprotocol provides at least one of: electric, magnetic, chemical, opticalor pharmaceutical treatment modulation of brain activity.
 16. The methodof claim 1, the method further comprising implanting a sensing subsystemconfigured to provide the neurostimulation device with sensed data. 17.The method of claim 1, wherein the at least one symptom of a braindisorder comprises a symptom that is associated with one of thefollowing: a major depressive disorder; bipolar disorder; dysthymicdisorder, anxiety disorder; panic disorder; posttraumatic stressdisorder; phobic disorder; psychiatric disorder psychosis;schizophrenia; and obsessive compulsive disorder.
 18. The method ofclaim 1 wherein the brain disorder is an obsessive-compulsive disorder,and wherein the brain network includes the anterior limbs of theinternal capsule, and wherein the first brain region of the brainnetwork includes the anterior limbs of the internal capsule and whereinthe second brain region of the brain network excludes the anterior limbsof the internal capsule.
 19. The method of claim 1 further includingoperating a patient programmer to modify linking rules of at least ofthe said stimulation protocols used by said stimulation subsystem.
 20. Aneurostimulation system for treating at least one symptom of a braindisorder comprising: a stimulation subsystem configured for providingbrain modulation of a brain network using least a first and a secondstimulator according to a treatment protocol; wherein the treatmentprotocol comprises: modulating a first brain region of the brain networkusing a first set of modulation parameters that determines modulationprovided by the first stimulator, said first set of modulationparameters designed to provide treatment of the symptom; modulating asecond region of the brain network using a second set of modulationparameters that determines modulation provided by the second stimulator,said second set of modulation parameters designed to provide stimulationto decrease a side-effect, resulting at least in part from modulation inthe first area; and, wherein, said brain network has at least one brainregion associated with the symptom for which treatment is sought. 21.The system of claim 20 wherein the system is further configured so thata first adjustment in at least one parameter used in the first set ofmodulation parameters causes a second adjustment in at least oneparameter the second set of modulation parameters.
 22. The system ofclaim 20 wherein said system further has a patient programmer whichallows modification of linking rules of a stimulation protocol used bysaid stimulation subsystem to modulate the second region of the brainnetwork.
 23. The system of claim 20 wherein said stimulation subsystemis configured to be implantable.
 24. The neurostimulation system ofclaim 20 further including a sensing subsystem configured for obtainingsensed data, and configured for evaluating the sensed data and formaking an adjustment to at least one of: said first set of modulationparameters said second set of modulation parameters; said treatmentprotocol, or linking rule parameters used by said treatment protocol,based upon evaluation of said sensed data.
 25. The neurostimulationsystem of claim 24 wherein said adjustment occurs according to a controllaw.